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2024 volumne 45 Issue 06

Cover - Table of Contents - Back Cover[0]

Abstract:

781| 525

2024 Headline[0]

Abstract:

547| 486

Evaluation on Site Selection of Shelters for Dam Failure Floods Considering the RiskDegree of Inundation Area[1-8]

LI Zongkun¹, ZHANG Kaikai¹, GE Wei^1,2, ZHU Junyu¹, JIAO Yutie¹, ZHANG Yadong¹

Doi:10.13705/j.issn.1671-6833.2024.06.016

Abstract: In response to the problem of insufficient attention to the risk degree of potential inundation areas in thesiting of shelters for dam failure floods, a new model for evaluating the sites of shelters was proposed. On the basisof establishing the risk evaluation index system, the improved catastrophe theory evaluation method was used to evaluate the risk degree and classify the risk level of the potential inundation areas. The distance between sheltersand high-risk level areas was taken as the site selection evaluation index, and the disaster risk, location scale, emergency support of shelters were considered. The weights were determined by AHP method, and the TOPSISmethod was applied to evaluate the sites of shelters. Finally, 13 potential inundation areas and 10 alternative shelters downstream of Luhun Reservoir in China were used as examples for validation. The results showed that amongthe areas with high risk levels, Baiyuan Township was a Class Ⅰ hazardous area, and Pengpo Township, MinggaoTownship, Chengguan Street, and Longmen Township were Class Ⅱ hazardous areas. The better evaluated shelterscould meet the requirements of paying attention to areas with high risk degree.

719| 617

Comparison and Analysis of Pedestrian Service Level Evaluation Modeling for theElderly at Signalized Intersections[9-17]

ZHANG Huiling, WANG Ruihao, ZHANG Rui

Doi:10.13705/j.issn.1671-6833.2024.06.022

Abstract: In order to analyze the needs of the elderly at the signalized intersection and evaluate the service level ofthe elderly pedestrians, a service level evaluation model based on subjective evaluation and intersection traffic characteristics was established. The traffic characteristic parameters of 33 signal-controlled crosswalks were obtainedthrough field observation and video analysis. A truncated questionnaire was used to obtain the subjective value ofpedestrian service level evaluation of the elderly crossing the street with synchronous conditions. The initial selection was based on nonlinear, linear and fuzzy linear regression models. Based on the data analysis of 30 crosswalks,Pearson correlation coefficient and Spearman correlation coefficient were used to identify the key factors affecting theservice level of the elderly crossing the street. Taking the key factors as input, comparing the nonlinear, linear andfuzzy linear regression models, the results showed that the multivariate nonlinear regression model of elderly pedestrian service level evaluation was better in terms of fit and error, and the data of 3 crosswalks in the verificationgroup further confirm the applicability of the model. The research results could provide some reference for the studyof traffic safety improvement strategies in the aging trend.

615| 517

Optimization of Sound Absorption Performance of OGFC Asphalt Mixture Based onAcoustic Parameters[18-24]

WU Wenliang, LI Chenyue, DAI Shenglin

Doi:10.13705/j.issn.1671-6833.2024.06.008

Abstract: In the phenomenological model, the sound absorption coefficient of porous materials was used to explaintakes into account the energy dissipation generated by the propagation of sound waves in the void structure. A modelbased on acoustic parameters was constructed to predict the sound absorption coefficient. In order to accurately obtain the five acoustic parameters ( porosity, flow resistance rate, tortuosity factor, viscous/ thermal characteristiclength) of OGFC asphalt mixture to construct the acoustic model, the OGFC asphalt mixture with different porosityand different gradation types was prepared by the combination of measurement and inversion, and the sound absorption coefficient was tested by standing wave tube. The flow resistance measurement equipment suitable for mixturewas developed. Based on the measured porosity, sound absorption coefficient and flow resistance, the inversionprogram was written based on genetic algorithm to invert the tortuosity factor and viscous/ thermal effect characteristic length of OGFC. Secondly, the finite element model of standing wave tube was established to verify the correctness of acoustic parameters. The influence of single factor of acoustic parameters on sound absorption performancewas analyzed. Finally, the sound absorption performance was optimized based on acoustic parameters. The resultsshowed that the higher the porosity of OGFC and the larger the nominal maximum particle size, the larger the average sound absorption coefficient and the peak sound absorption coefficient. The model constructed could better reflect the sound absorption characteristics of the mixture, and the peak sound absorption coefficient and the frequency of occurrence were consistent with the measured values. The increase of porosity, viscous characteristic lengthand thermal effect characteristic length, and the decrease of tortuosity factor would be beneficial to improve thesound absorption performance. The optimization results of the sound absorption performance of the mixture based onthe acoustic parameters showed that the porosity should be controlled at about 22% for the best sound absorptionperformance.

625| 591

Preparation and Performance Analysis of Bio-asphalt from Liquefaction andResinification of Straw[25-31]

DING Zhan^1,2, AN Linyu^1,2, LI Huifeng³, TIAN Chenxi^1,2, ZHOU Chunyu^1,2, LIU Fengkai^1,2

Doi:10.13705/j.issn.1671-6833.2024.06.011

Abstract: Waste wood, crop residues, livestock manure and waste oil, were widely used to produce bio-oil. Andthen partially or completely replace the petroleum-based asphalt. But the road performance of this asphalt was insufficient. In this study, the development of green and sustainable bio-asphalt to partially replace petroleum-based asphalt with wood-based phenolic resin made by straw liquefaction products was proposed. Firstly, the separation ofstraw components was carried out to extract cellulose and lignin. Straw and its primary components were liquefied toexplore the main factors influencing the liquefaction of straw. Then the liquefied products were combined with formaldehyde to synthesize lignin-based phenolic resin WPR. And the phenolic resin PR, which was obtained from thereaction with phenol, was compared and analyzed. Finally, the resin was put into matrix asphalt with different ratios to prepare bio-asphalt, and the performance of the bio-asphalt was analyzed by the three major indexes of eachbio-asphalt and viscosity. The results showed that the liquefaction rate of straw mainly depended on the liquefactionrate of cellulose, and its liquefaction reaction was complex, with a reaction kinetic level of 1. 71. From the resinyield and liquefaction products, WPR, PR FT-IR spectral analysis showed that the WPR resin synthesis rate washigher and had a better reactivity than the PR. Only when mixed with the liquefaction products, the performance ofthe bio-asphalt prepared was poorer. However, when mixed with WPR resin, the bio-asphalt′s high temperaturestability, low-temperature cracking resistance, deformation resistance, and temperature stability were better thanmatrix asphalt.

606| 598

Monthly Runoff Prediction Method Based on Secondary Decomposition and SupportVector Machine[32-39]

GAN Rong^1,2, MA Chaoxin^1,2, GAO Yong³, GUO Lin³, HOU Xiaoli⁴, LU Xueyong⁵

Doi:10.13705/j.issn.1671-6833.2024.06.003

Abstract: A monthly runoff prediction model( STL-VMD-SVM) based on a secondary decomposition using loess( STL) and variational mode decomposition (VMD) combined with a support vector machine( SVM) was proposed to address the nonlinear and non-stationary characteristics of runoff sequences. This model utilized STL to decompose the original runoff sequence into seasonal, trend, and residual terms of different frequencies and decomposedthe residual term into IMFs through VMD. An SVM model was established to predict seasonal, trend, and IMFs.The sum of the predicted values of all IMFs was the predicted value of the residual term, and the product of seasonal, trend, and residual terms was the final predicted value of the original runoff series. Based on the monthly runofftime series of Heishiguan Station and Gaocun Station on the mainstream of the Yellow River in the Yiluo River Basin, an example application and universality evaluation were conducted, and compared with the BP neural networkmodel and the long shortterm memory neural network model( LSTM) . The results showed that for the runoff prediction of Heishiguan Station in the Yiluo River Basin, the NSE, MAPE, RMSE, and R in the validation period of theproposed model were 0. 977, 13. 705%, 0. 327 and 0. 991, respectively, and their prediction accuracy was betterthan that of the single model and the primary decomposition model. The secondary decomposition of STL-VMDcould effectively improve the prediction accuracy of the model. The NSE, MAPE, RMSE, and R during the validation period in the runoff prediction at Gaocun Station on the mainstream of the Yellow River were 0. 979, 8. 509%,3. 263, and 0. 989, respectively, which also achieved good prediction results.

590| 593

Network Intrusion Detection Based on Spatial Features and GenerativeAdversarial Networks[40-47]

ZHANG Zhen¹, ZHOU Yicheng², TIAN Hongpeng¹

Doi:10.13705/j.issn.1671-6833.2024.06.001

Abstract: Address issues such as the inadequate consideration of inter-feature correlations in existing intrusion detection methods and the need for improved detection accuracy on high-dimensional discrete datasets, a network intrusion detection method MBGAN based on spatial features and generative adversarial networks was proposed. Initially, a transformation approach was devised to convert one-dimensional data into two-dimensional grayscale images, enabling convolutional kernels to capture richer contextual information. Subsequently, a bidirectional generative adversarial network model was employed for anomaly detection. The model was trained using network traffic images, incorporating the minimum Wasserstein distance and gradient penalty techniques to mitigate mode collapseand instability during generative adversarial network training. Experimental verification showed that the detection accuracy of the proposed method on the NSL-KDD, UNSW-NB15 and CICIDIS2017 datasets was 97. 4%, 92. 3% and94. 8%, the recall rates were 97. 2%, 93. 1% and 95. 6%, and the F1 were 97. 3%, 93. 0% and 95. 2%, respectively, which were better than those of other methods.

684| 598

Image Super-resolution Reconstruction Network Based on Double FeatureExtraction and Attention Mechanism[48-55]

BO Yangyu, WU Yongliang, WANG Xuejun

Doi:10.13705/j.issn.1671-6833.2024.03.009

Abstract: In the process of image super-resolution reconstruction, high frequency features might be ignored, whichwould lead to insufficient extraction features and fuzzy texture details in the reconstructed image. To solve this problem, an image super-resolution reconstruction network based on double feature extraction and attention mechanismwas proposed. In particular, in this study, a two-branch network for feature extraction was proposed to solve theproblem that high frequency features and multi-scale features could not be effectively extracted and uniformly fusedduring image reconstruction. In addition, in order to make the network obtain more accurate high-frequency features, a local spatial attention module was proposed, and combined with channel attention. A residual fusion attention module was constructed to improve the network′s ability to locate high-frequency features. Finally, the atrouspyramid module was designed to enlarge the receptive field of the network and enable the multi-scale feature extraction. Experiments were carried out on four benchmark datasets, and the results were better than the current advanced methods. Especially when the super-resolution multiple was 4, the proposed method improved the optimalPSNR by 0. 16, 0. 08, 0. 03 and 0. 20 dB, respectively, compared with the current mainstream models. The experimental results shown that the proposed method achieved better improvement in visual effect and quantitative analysis

671| 507

Semantic Matching Model for Chinese Scientific Datasets[56-64]

LIU Jianping^1,2, CHU Xintao¹, WANG Jian³, GU Xunxun¹, WANG Meng¹, WANG Yingfei¹

Doi:10.13705/j.issn.1671-6833.2024.03.008

Abstract: In order to address the difficulty of existing word-level semantic matching models in understanding sentence-level scientific dataset metadata, a sentence-level semantic matching ( CSDSM) model for Chinese scientificdatasets was proposed. The model used the CSL dataset to train and generate the CoSENT pre-training model basedon SimCSE and CoSENT. Building upon the CoSENT model, a multi-head self-attention mechanism was introducedfor feature extraction, and the final output was obtained by weighting the cosine similarity and KNN classificationresults. Experimental data from the National Earth System Science Data Center′s open semantic metadata information was used as a self-built scientific dataset. The experimental results showed that compared to the Chinese BERTmodel, the proposed model improved the Spearman′s ρ index by 0. 044 8, 0. 029 0, 0. 177 7 and 0. 050 9 on thepublic datasets AFQMC, LCQMC, Chinese-STS-B, and PAWS-X, respectively. Additionally, F1 and Acc on theself-built scientific dataset were improved by 0. 078 8 and 0. 063 4 respectively. The proposed model effectively addresses the problem of sentence-level semantic matching in scientific datasets.

572| 511

The Mobile Task Offloading Strategy for Allocating Physical Resources onDemand in Dynamic Cloud-edge Environment[65-74]

CAO Jie¹, JIA Lianhui¹, XU Jinchao²

Doi:10.13705/j.issn.1671-6833.2024.03.015

Abstract: Aiming at the unloading problem of mobile tasks for the limited edge server resources to maximize thesatisfaction of numerous mobile tasks with deadline requirements, a model for cloud-edge-device collaboration wasproposed to offload mobile tasks. Firstly, the model analyze the factors that affect the service demand of mobiletasks and the service guarantee of virtual machines, and give the measurement method, as well as the measurementmethod of the service matching degree between mobile tasks and virtual machines. Secondly, a mobile task offloading strategy was designed for on-demand allocation of physical resources in a dynamic cloud-edge environment.Based on the improved Hungarian algorithm, the purpose of this strategy was to find an offloading plan that couldmaximize service matching for a batch of tasks, and to further optimize the offloading plan by eliminating resourcecompetition through a limited number of iterations. Finally, the algorithm in this study was compared with theP2PITS algorithm, the ALBOA algorithm and the ESSDSA algorithm from many aspects. Experimental resultsshowed that compared with the P2PITS algorithm, the algorithm in this study reduced the virtual machine load rateby 30. 1%, the average waiting time by 13%, compared with the ALBOA algorithm, the algorithm in this study reduce the average completion time by 38. 6% on average, compared with the ESSDSA algorithm, the algorithm inthis study increased the execution success rate by 3. 5% on average. The proposed algorithm could effectively improve resource utilization and reduce the average completion time of tasks while meeting user deadline requirements.

532| 505

An Unsupervised Link Prediction Algorithm Based on an ApproximateGraph Neural Network Framework[75-82]

LI Gege^1,2, YE Zhonglin^1,2, CAO Shujuan^1,2, ZHOU Lin^1,2, WANG Xueli^1,2

Doi:10.13705/j.issn.1671-6833.2024.03.011

Abstract: For unlabeled networks, the link prediction method based on graph neural networks had poor performance when using its efficient modeling mechanism for link prediction tasks. An unsupervised link prediction algorithm (ALIP) was proposed. It could approximate the graph neural network framework to simulate the efficientmodeling mechanism and learning process of graph neural network algorithms, and to solve the problem of insufficient modeling caused by missing network node labels. Firstly, referring to the input layer of GCN, the structuralinformation and node attributes of the network were fused. Secondly, matrix factorization is used to replace the hidden layer of GCN and simulate forward propagation. Then the ideas of identity mapping and vector optimization toachieve vector transformation and model optimization to obtain the network node representation vector, which wereused to simulate the back propagation of GCN. Finally, the similarity matrix for performance evaluation of link prediction tasks was calculated. On the Citeseer dataset, DBLP dataset and Cora dataset, the experimental resultsshowed that ALIP algorithm had a maximum AUC value of 98. 01%, and its performance was superior to the other23 link prediction algorithms. The effectiveness and feasibility of the algorithm, in this study provide a new solutionfor complex unlabeled network link prediction tasks.

612| 577

A SICR Rumor Propagation Model with Time Delay and Enforced Silence[83-91]

LU Youjun, WU Sen, WEI Jiayin, DENG Li, LUO Shasha

Doi:10.13705/j.issn.1671-6833.2024.06.021

Abstract: Considering the factors such as time delay in the propagation of rumors and the inability to spread rumorsdue to the forced silence of network regulators, in this study, based on the SIR model, combined with the rumorrefuging mechanism and the space theory, nodes in the network were divided into susceptible node S, infectivenode I, rumor-refuging node C and recovered node R, a new SICR rumor propagation model was proposed. Firstly,the dynamic equation of rumor propagation in homogeneous network structure was given by means of average fieldtheory, the existence of equilibrium point was analyzed, and the basic reproduction number of the model was calculated by using the next generation matrix method. It was found that the basic reproduction number was related to thepropagation rate, average degree, migration rate, migration rate, forced silence rate, and recovery rate of infectivenodes. Secondly, the local asymptotic stability of the equilibrium point was analyzed by Routh-Hurwitz criterion,and the global asymptotic stability was analyzed by LaSalle′s invariance principle. Finally, the correctness of thetheoretical results was verified by numerical simulation experiments. The simulation results showed that SICR modelconsidering the rumor-refuting mechanism could suppress the rumor propagation better than SIR model. Based onDataset_R6 dataset, the parameters of the model were fitted by least square method, and the R2of the model was0. 950 8.

582| 547

Analysis of Key Risk Factors and Coupling Effects of Construction Safety ofHigh-rise Buildings[92-99]

CHENG Lianhua, YANG Yaoyan, LI Shugang, WEI Kai, CAO Dongqiang

Doi:10.13705/j.issn.1671-6833.2024.06.006

Abstract: In order to explore the key risk factors of high-rise building construction safety and the coupling effects ofrisk elements, the complex network model and the N-K model were combined, 158 high-rise building constructionaccident cases from 2015 to 2022 were selected according to the completeness of the accident case investigation report, and the causes of 84 of them were coded according to the grounded theory, and 5 risk elements including human, machine, material, pipe and environment and 23 risk factors were identified through statistical analysis. Thecoupling risk values of various coupling forms of risk elements were calculated according to the N-K model, and thedegree value distribution of each risk factor in the complex network model was obtained by using Ucinet software.The risk coupling network model of high-rise building construction was drawn by Netdraw, and the potential riskchain of nodes of 23 risk factors was analyzed, and the coupling form of potential risk chain and the coupling degreevalue of N-K model were combined to modify the standardized output. The remaining 74 accident cases were used toverify the results, and the verification results were roughly consistent with the previous 84 accident cases. The results showed that the greater the number of risk elements involved in coupling, the greater the risk coupling value,and the coupling form involving equipment elements had the largest coupling value. The lack of site management,the lack of safety education and training, the incompleteness of safety management system, inporper wearing of protective equipment, and the lack of investigation and management of hidden danger were the key risk factors thatneed to be focused on prevention and control.

548| 634

Large Eddy Simulation of Wind Load Interference Effects on Tandem DoubleHemispherical Domes with Different Spacing[100-106]

ZHENG Deqian¹, YAN Wei¹, LI Liang¹, ZHAO Lingyu², MA Wenyong³

Doi:10.13705/j.issn.1671-6833.2024.06.009

Abstract: Based on the spatially-averaged large eddy simulation method, the wind interference effect of the tandemdouble hemispherical domes was numerically studied considering different center spacing. The effectiveness of thepresent numerical simulation method and parameter settings was firstly verified by comparison between results oflarge eddy simulation and the wind tunnel test on the tandem double hemispherical dome with center spacing of160 m. Then the wind pressure distribution characteristics on the tandem double hemispherical domes surface withthe center spacing of 160 m and 190 m were compared and analyzed to study the influence of the interferenceeffect. In conjunction with the simulated unsteady flow field, the mechanism of the influence on wind loads withdifferent center spacing was investigated. Similar tendency was observed for the distribution of the mean and fluctuating wind pressure coefficients of the tandem double spherical shell roof with different center spacing. The blockingeffect of the upstream roof weakened the positive pressure on the windward surface of the downstream roof. However, the blocking effect of the downstream roof would intensify the flow separation of the upstream roof when thespacing was small, resulting in a significant increase in the local wind suction on the top skylight. As the spacingincreased, the separated vortex on the leeward surface of the upstream roof could change from small-scale strip vortex to large-scale arc-shaped one, leading to more significant wind pressure fluctuations on the roof skylight, upstream leeward surface, and downstream windward surface.

505| 496

Geological Modeling Interpolation Algorithm Considering Spatial Anisotropy of Strata[107-113]

YU Junjian¹, MIN Haokun², WANG Feifei¹, LI Jian²

Doi:10.13705/j.issn.1671-6833.2024.06.002

Abstract: To address the issues of insufficient precision, inadequate representation of regional characteristics, andthe lack of consideration for geological spatial anisotropy in traditional geological modeling interpolation algorithms,in this study a three-dimensional geological interpolation method was proposed to take into account geological spatialanisotropy. Building upon the traditional IDW interpolation, this method involved constructing virtual boreholes,simulating the creation of an original stratum point set, and adjusting the parameters of the IDW interpolation ellipsesearch range to ultimately achieve an adaptive transformation of the optimal search parameters. Additionally, in thisstudy the concept of " directional marker points" was introduced to achieve a secondary optimization of the searcharea through " expansion" and " collapse" . Geological borehole datas from the Zhengzhou Urban Active Fault Detection Project, were used to analyze the regional adaptability of each algorithm layer by layer, implement the implicit surface representation of the three-dimensional geological model, and conduct cross-validation with commonlyused interpolation algorithms. The experiment results demonstrated that the proposed method possessed good regional adaptability and could effectively represent the anisotropic characteristics of urban underground spatial structures.While ensuring interpolation accuracy, it could effectively expresse the actual extension of strata within the region.

546| 533

Multi-unit Wind Power Prediction Based on Long Short-term Memory andParticle Swarm Optimization[114-121]

WU Zhenlong¹, MO Yipeng¹, WANG Ronghua², FAN Xinyu¹, LIU Yanhong¹, GUO Xiaolian³

Doi:10.13705/j.issn.1671-6833.2024.06.005

Abstract: At present, the manual adjustment of hyper-parameter for current wind power prediction model was slowand unreliability. In order to achieve the prediction effect, the model used in wind power prediction needs to selectthe appropriate hyper-parameters for the model. Based on this, in this study, a multi-unit wind power predictionmodel was proposed based on long short-term memory ( LSTM) . Firstly, the Spearman correlation method was usedto quantitative analysis. Secondly, the principal component analysis ( PCA) was used to reduce the dimension ofthe input features as well as extract the key information. In addition, considering the difficulty of choosing parameters for LSTM, in this study, particle swarm optimization ( PSO) algorithm was used to optimize the number of hidden layer neurons in each layer of LSTM. For the problem of wind power prediction of multiple units, in this study,a single wind turbine was used to find the most excellent model in a single unit, and applied the prediction model tomulti-unit prediction. Experiments showed that compared with other models, the root mean square error of the proposed method was reduced by 11. 8%, and the mean absolute error was reduced by 5. 03%.

638| 622

Analysis and Evaluation Model of Smart Grid Operation State Basedon Graph Neural Network[122-128]

LIU Huilin¹, FAN Ruiming¹, CHENG Dachuang², PENG Long¹, ZHANG Guoliang¹, ZHANG Zhaogong³

Doi:10.13705/j.issn.1671-6833.2024.06.017

Abstract: The safe operation of smart grid was the primary premise to ensure continuous and efficient power supply. Therefore, a graph neural network (GNN) based power system operation state analysis and evaluation modelwas proposed. Firstly, long short-term memory network was used to fill missing data, to ensure that the model hadgood performance in stability assessment and fault location. Secondly, a binary classifier for evaluating the stablestate of power grid operation and a multi classifier for locating faulty components were designed based on GNN. Dueto the ability of the proposed model to fully explore the spatiotemporal characteristics of power grid operation data,the proposed model exhibited superior performance compared to other methods under different measurement conditions. Experimental results showed that when the time series length of data was 0. 1 seconds, the stability assessment and fault location accuracy of the proposed model were 0. 985 5 and 0. 981 4, respectively, and higher thanthe comparative models. When only half of the component data can be measured, the accuracy of the proposedmodel for stability assessment, bus fault location, and generator fault location were 0. 998 0, 0. 960 9, and0. 981 2, respectively, and higher than the comparative models.

618| 556

Operation and Maintenance Decision of Compressor Water Wash Based on Digital Twin[129-136]

TAN Zouqing¹, DU Chenyu^1,2, WAN Anping²

Doi:10.13705/j.issn.1671-6833.2024.03.013

Abstract: In order to improve the power generation efficiency of the gas turbine,and to solve the problem of thehigh cost of the operation and maintenance (O&M) of the compressor water washing system, a digital twin-basedO&M decision study of the compressor was conducted. And a health management framework for gas turbine in power plants based on digital twin was proposed. Based on that the compressor operation data was processed, and theextreme gradient boosting algorithm was used to build a prediction model for the washing cycle, and some of the parameters within the dataset were selected as inputs to the model, with the gas consumption as the output quantity,analyzed the change rule and its relationship with the input quantity. the water washing cycle and water washing recovery rate were calculated and compared, and the appropriate water washing cycle for O&M decision of the compressor was derived. The model prediction results showed that: the average R2_score of the eight water washing gasconsumption prediction reached 0. 98, and the prediction results were accurate. Among the eight times of waterwashing, the second and third water washing cycles were appropriate, and the third water washing recovery rate wasoptimal, resulting in the guiding hours of gas turbine compressor water washing cycle of 1 824 hours. Comparedwith the average water washing cycle of the power plant in the actual implementation, the cost of water washingcould be reduced by 21. 9 million yuan per time.

542| 587

Analysis of Particulate Matter Emission Characteristics of Commercial BiomassPellet Combustion[137-142]

YANG Wei¹, FENG Shilong¹, XIN Shanzhi², LI Heyong¹, HAN Yong³, ZHU Youjian¹

Doi:10.13705/j.issn.1671-6833.2024.06.004

Abstract: In order to investigate particulate matter ( PM) emission characteristics from the combustion of commercial biomass pellet, a fixed-bed reactor was used to conduct combustion experiments of wood dust, cotton stalk andbamboo dust. The particle size distributions and main element composition of PM were analyzed. And the influenceof element content on PM emission was discussed. It was found that the yields of PM10from high to low was cottonstalk, wood dust and bamboo dust, and the yields were 27. 76, 20. 83 and 9. 65 mg / m3, respectively. The PMswere mainly composed of submicron particles ( PM1 ) , and the proportion of PM1to PM10 was more than 90%. PM1was mainly composed of alkali metal chloride and sulfide, while PM1-10 was mainly composed of compounds formedby calcium magnesium silicate. Correlation analysis showed that there was a positive correlated between biomass ashcontent and PM1yield, while the content of Mg +Ca and n ( Mg +Ca) / n ( Si) were linearly correlated with PM1-10 yield.

605| 504

Pre-publication

Frequency Control Strategy of Photovoltaic Participation in Power System Based on TD3 Algorithm[9]

ZHANG Jianhua, TAO Ying, ZHAO Si

Doi:10.13705/j.issn.1671-6833.2024.06.023

Abstract: Addressing the challenges posed by the intermittency and randomness of photovoltaic power output to maintaining system frequency stability, this paper proposes a rapid frequency regulation method based on deep reinforcement learning. This method does not require a specific mechanistic model and is suitable for solving strong uncertainty problems related to photovoltaic power generation. Firstly, a simplified photovoltaic power generation system model is constructed in this paper. Subsequently, a novel frequency controller is designed based on the twin delayed deep deterministic policy gradient algorithm. To verify the effectiveness of the proposed control strategy, it is compared with traditional droop control, sliding mode control, and a control strategy based on the deep deterministic policy gradient algorithm. The simulation results show that the performance indicators of the proposed control strategy are excellent, such as the maximum frequency deviation is lower than that of other control algorithms, which fully verifies the effectiveness and superiority of the proposed control strategy after applying two different load disturbances

106| 110

Research on Vehicle Yaw Stability Analysis Method Based on State Estimation[8]

KOU Farong,CHANG Hangtao, WANG Qianlei, FANG Bo

Doi:10.13705/j.issn.1671-6833.2024.06.015

Abstract: Aimed at the problem that the state parameters were difficult to obtain and the analysis results were single in the process of vehicle yaw stability analysis, a two-degree-of-freedom vehicle model was established as a reference model for yaw stability analysis and state estimation. The phase plane was constructed by using the sideslip angle and its angular velocity to analyze the yaw stability of the vehicle, and the adaptive phase plane stability domain based on multi-layer perceptron ( MLP ) was designed. According to the real-time state of the vehicle and the phase plane stability region, the yaw stability evaluation index was constructed. A vehicle state estimation algorithm based on extended Kalman filter (EKF) was designed, and a vehicle yaw stability analysis method based on state estimation was proposed. In order to verify the effectiveness and practicability of the proposed yaw stability analysis method, simulation tests at 100km/h and real vehicle tests at 30km/h were conducted under double lane change conditions. The simulation and real vehicle test results showed that the average error of sideslip angle estimation based on state estimation was less than 0.1°, and the average error of longitudinal velocity estimation was less than 0.03 m/s. This method could quantify the yaw stability from 0 to 1 based on the estimated vehicle state parameter input, reflecting the dynamic changes in vehicle yaw stability

136| 86

A Method for Optimizing Mountainous Highway Routes Based on Data Optimization Multi-Attribute Decision Model[10]

GE Wei, PENG Zh aohui, XU Bo, Liu Mu, WANG Yawei, ZHANG Yadong, WANG Siwei

Doi:10.13705/j.issn.1671-6833.2024.06.020

Abstract: There are problems in the optimization of mountainous highway routes, including complex evaluation indicators, difficulty in quantifying qualitative indicators, and the weight of subjectively set indicators do not match the actual situation. This article is based on the principles of technology, economy, and safety, referring to the Hall three-dimensional structure to analyze the influencing factors of mountainous highway routes, and constructs an evaluation index system. Introduced Cloud Model theory to quantify qualitative evaluation indicators, and used the Variable Weight theory to modify the constant weight of evaluation indicators considering the impact of the actual state of evaluation indicators on the evaluation results. Finally, a method for optimizing mountainous highway routes based on TOPSIS is proposed . This method was applied to the optimization of routes for the fourth risk point of the Alcia Highway Project in Bolivia. The results indicate that cloud models can effectively solve the problem of uncertainty in qualitative indicators, which makes them difficult to quantify; The closeness degree of the three route schemes is 0.833, 0.606, and 0.684, respectively. Compared with traditional constant weight, the variable weight theory highlights the influence of extreme indicators on the evaluation results in the evaluation process, and the results are more realistic

97| 104

Task Offloading Strategy of UAV Edge Computing Based on Deep Reinforcement Learning[10]

WANG Feng, MA Xingyu, MENG Pengshuai, ZHAO Wei, ZHAI Weiguang

Doi:10.13705/j.issn.1671-6833.2025.01.018

Abstract: Aiming at the problems such as lack of infrastructure, high task delay and high bandwidth demand in complex geographical conditions, this paper proposes a multi-stage mobile edge computing system model which combines computing offload and power distribution. In this model, a server equipped with MEC is deployed near the UAV to provide computing services, and the problems such as task offloading, power consumption and computing resource allocation of the UAV are comprehensively analyzed and the measurement methods are given. At the same time, the types of tasks that the UAV can perform and the requirements of the CPU and GPU on the UAV are considered. The problem is expressed as a mixed integer nonlinear problem. Secondly, a task computing offloading algorithm based on deep reinforcement learning is proposed to solve this problem. Based on the improved double deep Q learning algorithm, the algorithm uses deep neural network to find the mapping between drones in deep reinforcement learning, find potential patterns from the state space and estimate the optimal action, and uses model-free DRL method. Enable each drone to make quick unloading decisions based on local observations. In order to verify the effectiveness of the proposed scheme, detailed simulation is carried out in this paper. Simulation results show that the proposed algorithm reduces the average unloading cost by 42.8% compared with LCGP algorithm. Compared with DDPG algorithm, the energy consumption is reduced by 16%. Compared with DDQN algorithm, the task execution delay is reduced by 12.9%

210| 90

Research on Dynamic Grouping Active Equalization of Series Batteries Based on Reconfigurable Circuits[2]

QIN Dongchen, ZHAO Hongfei, WU Hongxia, YANG Junjie, CHEN Jiangyi, WANG Tingting

Doi:10.13705/j.issn.1671-6833.2024.05.003

Abstract: In order to solve the problem of inconsistent state of charge (SOC)of single cells in battery pack, the active equalization control technology is studied with series battery pack as the research object. The research content included the improvement of the balancing topology and the design of the balancing control strategy. Firstly, a new topology is proposed and verified. Secondly, the mathematical model of equalization circuit is established, and the effects of voltage difference and switching frequency on equalization performance are analyzed. According to the results of voltage difference analysis, a multi-cell-to-multi-cell balancing control strategy based on variable duty cycle is designed to improve the equalization speed and consistency of battery pack. Finally, the joint simulation of equalization topology and equalization strategy is carried out in MATLAB/Simulink. The results show that, compared with the fixed group balancing control strategy, the proposed balancing topology and control strategy can improve the balancing speed and consistency of the battery pack, the time efficiency is increased by 29.71%, the battery SOC variance is reduced by 16.13% and the number of energy transfers is reduced by 52.5%

139| 251

Automated penetration testing method based on deep reinforcement learning Noisy Net-A3C algorithm[2]

DONG Weiyu1, LIU Pengkun2, LIU Chunling1, TANG Yonghe1 , MA Yupu 2

Doi:10.13705/j.issn.1671-6833.2024.02.011

Abstract: In the field of automated penetration testing, most existing attack path decision algorithms are based on partially observable Markov decision processes (POMDP), which have problems such as high algorithm complexity, slow convergence speed, and susceptibility to getting stuck in local optima. This article proposes a reinforcement learning algorithm NoisyNet-A3C based on Markov Decision Process (MDP) and applies it to the field of automated penetration testing. This algorithm trains Actor Critic through multiple threads, and the operation results of each thread are fed back to the main neural network. At the same time, the latest parameter updates are obtained from the main neural network, fully utilizing computer performance, reducing data correlation, and improving training efficiency. In addition, adding noise parameters and weight network training update parameters to the training network increases the randomness of the behavior strategy, facilitates faster exploration of effective paths, reduces the impact of data disturbances, and enhances the robustness of the algorithm. The experimental results show that compared with A3C, Q-learning, DQN, and NDSPI-DQN algorithms, the NoisyNet-A3C algorithm converges more than 30% faster, verifying that the algorithm proposed in this paper converges faster

254| 235

Mechanism Analysis of Soil Compaction Grouting Based on Modified Cam-clay Model[2]

XING Haipeng1,2, WU Guanghua1,2, WANG Ge1, CHEN Kunyang1, LI Xiaolong1, ZHANG Bei1

Doi:10.13705/j.issn.1671-6833.2025.01.004

Abstract: The existing compaction grouting simulation method can only analyze the stress distribution after grouting, and cannot obtain the parameter information reflecting the compaction effect of grouting, such as the void ratio and density of soil after compaction. Therefore, the MCC is introduced to describe the mechanical property of soil, and based on the elastic-plastic finite element theory, a simulation method is established to simulate the compaction grouting process of constant density slurry in soil. A more comprehensive and intuitive description of the formation compaction effect is achieved. The compaction grouting simulation analysis was carried out on clay, silty clay and other low permeability soil. Compared with the analytical and experimental results, t he overall average relative errors of the simulated values and analytical solutions of radial stress and void ratio under different grouting pressures are 4.04% and 0.29% respectively , and the average relative errors between the calculated elastic modulus and void ratio and the field test results are 2.85% and 5.69% respectively, which proves the applicability of this method. On this basis, the distribution characteristics of soil density, void ratio and elastic modulus around the grouting column after grouting reinforcement are analyzed. The results show that when the grouting pressure increases from 0.4 MPa to 1.0 MPa at the grouting depth of 1.5 m, the soil density, elastic modulus and void ratio at the grouting hole center of 0.05 m approximate linear changes, and the average change rates are 0.148 g/cm3/MPa, 0.808 and -0.126 MPa-1, respectively. When the grouting pressure is 0.4 MPa, the increase rates of soil density and elastic modulus and the decrease rate of void ratio at 0.05 m from the center of the grouting hole gradually decrease with the increase of grouting depth. Overall, the density and elastic modulus of the soil around the grouting column are greatly increased after grouting reinforcement, and the void ratio is significantly reduced. The soil parameters change less with the distance from the grouting hole, and gradually return to the initial state. Under the same grouting pressure condition, with the increase of grouting depth, the compaction effect gradually weakens

285| 408

Short Term Wind Power Forecasting Based on Improved Dung Beetle Optimization Algorithm[2]

JIANG Jiandong1, ZHANG Haifenf1,2GUO jiaqi2

Doi:10.13705/j.issn.1671-6833.2025.01.015

Abstract: A short-term wind power prediction model based on POTDBO-VMD-CNN- BiLSTM is proposed in the thesis to improve the accuracy of short-term wind power prediction. Firstly, three strategies are adopted to improve the dung beetle optimization algorithm, including integrating Piecewise chaotic mapping, integrating Osprey optimization algorithm, and integrating adaptive T-distribution perturbation, in order to balance the global exploration and local development capabilities of the dung beetle optimization algorithm and accelerate its convergence speed . Secondly, the improved Dung Beetle Optimization algorithm ( POTDBO) is used to optimize the decomposition number and penalty factor of Variational Mode Decomposition (VMD) to improve the decomposition effect of VMD. Then, the POTDBO-VMD model is used to decompose the wind power . Finally, the decomposed frequency components and residual components are input into the CNN-BiLSTM hybrid model for prediction, and the prediction results of each frequency component and residual component are sequentially reconstructed to obtain the wind power prediction results. The proposed model is experimentally tested using actual data from wind farm s in Xinjiang and Jilin . Compared with the CNN-BiLSTM model , the results show that the model in this thesis increases by 4.21% and 7.14% on R 2 respectively, demonstrating better prediction accuracy demonstrates better prediction accuracy

249| 378

Steel Surface Defect Detection Based on Improved YOLOv5 Algorithm[2]

YAN Yu，JING Yuchao，SHI Mengxiang，YANG Duo

Doi:10.13705/j.issn.1671-6833.2025.01.007

Abstract:

In order to solve the problem of low efficiency of steel defect detection and economic loss caused by false detection, an improved YOLOv5 algorithm was proposed for steel defect detection.Under the condition of keeping the original YOLOv5 detection layer unchanged, the improved algorithm added three auxiliary branches with adaptive weights to extract the shallow information of the YOLOv5 network, and the auxiliary branches could also enhance the gradient flow of the whole network, which made the training effect better. The EMA attention mechanism was added to the main part of the network, and the weighted feature information of the EMA module could help the model better focus on and understand the important target features. SIoU was used instead of the CIoU loss function, and the angle loss and shape loss introduced by SIoU could make the anchor frame more fast and accurate in the regression process to improve the stability and robustness of the detection. Through experiments on the NEUDET dataset, the proposed algorithm had an accuracy improvement of 3. 7 percentage points compared with the original YOLOv5s, and had better detection performance than other mainstream algorithms.

275| 362

Modulation Recognition Algorithm Based on Multi-Criteria Fusion and Intelligent Decision[2]

XIA Zhaoyu, LIN Yujie, HU Chunyuan, WU Zihao

Doi:10.13705/j.issn.1671-6833.2024.04.015

Abstract: Aiming at the requirement of high modulation order identification and the difficulty of modulation identification in low signal-to-noise ratio environment in 6G communication, a modulation recognition algorithm based on multi-criteria fusion and intelligent decision was proposed by combining artificial intelligence technology and modern signal processing technology. The algorithm was divided into two parts: multi-criteria fusion network and intelligent decision network. The multi-criteria fusion network calculated the higher-order cumulative extensions of the standard modulation signals, traversed all the potential thresholds by using local optimal solutions, and determined the judgment thresholds by Gini coefficient and the entropy of certainty gain. The intelligent decision network adopted a CART architecture to recognize the modulation format of unknown signals using the determined judgment thresholds, and the model was iterative optimized using a pruning algorithm to obtain the finally optimal decision tree, forming a modulation recognition algorithm based on multi-criteria fusion and intelligent decision making. Experimental results showed that the algorithm could accurately recognize 16QAM, 64QAM, 128QAM, 1024QAM, 2PSK, 4PSK, 8PSK, 2FSK, 4FSK at 0dB SNR, and the comprehensive recognition accuracy reached 99.4%. Compared with other methods, the modulation recognition accuracy and the types of recognizable modulation have been improved

188| 285

COP-based Feature Extraction and Analysis of Plantar Pressure in Tai Chi Stake[2]

WAN Hong1,2, GU Zhi yuan1,2, LI Mengmeng1,2

Doi:10.13705/j.issn.1671-6833.2025.01.016

Abstract: To explore the inherent characteristics of Tai Chi Stake training and digitally interpret its movement essentials, effective plantar pressure detection equipment was used to collect plantar pressure signals from participants, and the relative position, time-domain, frequency-domain, and regularity indicators of the center of pressure (COP) movement between the expert group and the trainee group were compared and analyzed. The results show that the relative position of COP of the expert group is closer to 50% compared to the trainee group. In terms of time-domain indicators, the root mean square of COP movement of the expert group is significantly larger than that of the trainee group in both the left -right and front-back directions, while the frequency-domain peak frequency of the movement is significantly lower than that of the trainee group in both directions. For the sample entropy analysis of COP that measures the regularity, the expert group showed significantly lower values in both the left-right and front-back directions compared to the trainee group. These results indicate that the Tai Chi Stake COP of the expert group is more concentrated in the central position, reflecting the technical essential of " stand straight and be centered". The regular low-frequency adjustment reflects the characteristic of " motion in quiescence" in Tai Chi Stake

361| 449

HE L. Key Target Person Detection and Tracking Based on Fragmented Video Information[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2023[2]

MA Liuyang1, HU Zhengzheng1, LI Wuhua1

Doi:10.13705/j.issn.1671-6833.2025.01.017

Abstract: To address the problem of target identity (identification, ID) fluctuation during target tracking, affecting the time-sensitive target recognition, this study proposed an "detection-decision" time-sensitive target recognition method (AR-SSVEP-YOLOV3) that integrates augmented reality (AR) technology, steady-state visual evoked potentials (SSVEP), and YOLOv3. The target perception module obtains the front-end scene video and presents it in real-time through an AR headset. The YOLOv3 algorithm completes the detection of sensitive targets in the scene video, and the AR-SSVEP EEG processing module decodes the EEG data of the subject during ID changes to identify time-sensitive targets. The correct recognition rate of time-sensitive targets is compared and analyzed, and the average improvement in the recognition rate of AR-SSVEP-YOLOV3 time-sensitive target recognition method compared to the YOLOv3 algorithm is about 40%, and the average improvement compared to the YOLOv3-Sort algorithm is about 15%. The experimental results show that the AR-SSVEP-YOLOV3 time-sensitive target recognition method can reduce the influence of target ID fluctuation on time-sensitive target recognition and improve the human-computer interaction ability and the correct recognition rate of time-sensitive targets.

262| 263

A Path Planning Method for Parallel Parking in Constrained Parking Channels[2]

QIN Dongchen, ZHANG Wencan, WANG Tingting, CHEN Jiangyi

Doi:10.13705/j.issn.1671-6833.2024.05.006

Abstract: Aiming at the problem of long time and low success rate of automatic parking planning in restricted parking channels, an improved hybrid A * algorithm for path planning is proposed. Firstly, the parking path is divided into two parts: the forward pose adjustment section and the backward reverse parking section. Secondly, the collision risk cost is introduced into the hybrid A * algorithm, the node expansion method is improved, and the collision detection is carried out by judging whether the vehicle contour line intersects with the obstacle line, so as to improve the real-time and safety of the parking segment planning. Finally, the objective function is designed with the path length, smoothness and deviation as indexes, and the initial path is smoothed by quadratic programming to get the final path. The improved algorithm and the original algorithm are simulated by MATLAB. The results show that the improved algorithm can obtain a smooth and collision-free parking path under the constrained parking channel, and the search time is reduced by 23.8% compared with the hybrid A * algorithm, and the obtained path is safer and easier to track.

269| 456

Dynamic Fusion of Attention Mechanism Imputation Model forMissing Data of Power Load[1-8]

ZHAO Dong, LI Yarui, WANG Wenxiang, SONG Wei

Doi:10.13705/j.issn.1671-6833.2024.05.004

Abstract: In order to improve the accuracy of missing value filling of power load data and ensure the efficient follow-up data analysis and application, a filling model based on dynamic fusion attention mechanism is proposed. The model consists of an attention mechanism module and a dynamic weighted fusion module, and the deep association between features and timestamps is mined through two different attention mechanisms of the attention mechanism module. The learnable weights are assigned to the two outputs of the attention mechanism module by the dynamic weighted fusion module to get the feature representation. Finally, the feature representation is used to replace the values at the missing positions to obtain accurate filling results. The proposed model is validated using the meteorological and load dataset of a certain area of New York City and the UCI power load dataset, and the experimental results show that DFAIM has certain advantages over statistical, machine learning, and deep learning filling models in MAE, RMSE, and MRE.

296| 417

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A Survey on Genetic Programming to Image Analysis[3-13]

Bi Ying,Xue Bing,Zhang Mengjie

Doi:10.13705/j.issn.1671-6833.2018.06.018

Abstract: As an evolutionary computation (EC) technique, Genetic programming (GP) has been widely applied to image analysis in recent decades. However, there was no comprehensive and systematic literature review in this area. To provide guidelines for the state-of-the-art research, this paper presented a survey of the literature in recent years on GP for image analysis, including feature extraction, image classification, edge detection, and image segmentation. In addition, this paper summarised the current issues and challenges, such as computationally expensive, generalisation ability and transfer learning, on GP forimage analysis, and pointd out promising research directions for future work.

7817| 4093

A New Cryptophane A-coated SAW Methane Gas Sensor[6-23]

Wang Wen1,Hu Haoliang1,He Shitang1,Pan Yong2,Zhang Caihong3

Doi:10.13705/j.issn.1671-6833.2016.03.026

Abstract: In view of the current situation that the traditional methane sensor technology is difficult to imple-ment the field detection and monitor on methane gas, a novel room-temperature SAW methane gas sensor coa-ted with cryptophane-A sensing interface is proposed by utilizing the supermolecular compound cryptophane-A’ s specific clathration to methane molecules. The sensor was composed of differential resonator-oscillators with excellent frequency stability, a supra-molecular CrypA coated along the acoustic propagation path, and a frequency acquisition module. The supramolecular CrypA was synthesized from vanillyl alcohol using a three-step method and deposited onto the surface of the sensing resonators via dropping method. Fast response and excellent repeatability were observed in gas sensing experiment, and the estimated detection limit and meas-ured sensitivity in gas dynamic range of 0 . 2% ~5% was evaluated as ~0 . 05 % and ~184 Hz/%, respec-tively. The measured results indicated the SAW sensor was promising for under-mine methane gas detection and monitor.

6954| 4134

Urban Optimal Capital Structure Analysis based on Random Forest and Multi-objective Particle Swarm Optimization[14]

Li Yanyan 1,Yang Haotian 2,Zeng Yufan 3

Doi:10.13705/j.issn.1671-6833.2019.04.028

Abstract: Urban capital structure was a complex?problem affected by multi-factors and multi-objective particle.This paper attempt ed to explore a scientific and appropriate d algorithm to construct the optimal capital structure model under the influence of multi-objective and multi-factors to analyze the situation of urban capital structure.First, the data in history could find the relationship among features of the data in history by using the regression characteristics of random forest. Then, the multi-objective particle swarm optimization algorithm was used to find values of the features that achieve the best results according to the existing relationship features. Then finding the most correlate data from the historical data based on the best eigenvalues of these effects. Therefore, the cities and the years with relatively better capital structure allocations are analyzed. We could play a good role in the reference and development of each city by continuously learning these superior structural configurations

6918| 3434

Numerical Simulation of Multi-phase Flow Mixing in Stiring Tank Based on EDEM-FLUENT Coupling[79-84]

Wang Jianming; Qiu Qinyu; He Xunchao

Doi:10.13705/j.issn.1671-6833.2018.05.015

Abstract: By means of EDEM-FLUENT simulation and VOF(Volume of Fluid) method and Euler-Lagrangian model, a mixture model of discrete solid, continuous liquid and gas phase was constructed to simulate the three-phase flow with solid-liquid-gas in a stirring tank. The effect of the moving state of solid particles in stirring tank and free liquid level were explored. The gas-liquid continuous phase modeling based on VOF method using FLUENT software could capture gas-liquid interface well and the model was closer to the actual working condition. Based on the Discrete Element Method(DEM), the discrete element modeling of solid particles was established and its position information in the tank was simulated intuitively by the joint simulation of the two software. The dispersion of solid particles was consistent with the results obtained by Euler method.

6663| 3505

Semi-coupled Dictionary Learning Super-resolution Reconstruction Model with Detail Constraint Factor[59]

Huang Yuda; Wang Yanran; Niu Sijie;

Doi:10.13705/j.issn.1671-6833.2021.03.010

Abstract: In order to improve the super-resolution reconstruction quality of single image, an improved learning based super-resolution approach was proposed in this paper. To tackle the problem of low details of semi-coupled dictionary learning super-resolution algorithm, the paper presented learning strategy where detail constraint factor and semi-coupled dictionary learning were performed in turn. In reconstruction stage, detail constraint factor was designed by the gradient in both horizontal and vertical direction. Combined with semi-coupled dictionary learning, detail constraint factor was used to further improve the super-resolution reconstruction quality. In order to improve the contribution of detail constraint factor on preserving boundary information, the adaptive regular parameter was explored via the approximate Laplacian distribution of edge difference. Compared with the semi coupled dictionary learning super-resolution algorithm, the peak signal-to-noise ratio of this method was increased by 1.5% on average. Experiments demonstrated that the proposed method could achieve better reconstruction effect in both subjective and objective evaluation and improve the quality of super-resolution.

6605| 1046

Research on Speech Recognition Based on Improved LSTM Deep Neural Network[63-67]

Zhao Shufang, Dong Xiaoyu

Doi:10.13705/j.issn.1671-6833.2018.02.004

Abstract: The language model based on neural network LSTM structure, the LSTM structure used in the hidden layer unit, the structure unit comprises a memory unit which can store the information for a long time, which has a good memory function for the historical information. But the LSTM in the current input information state9 does not affect the final output information of the output gate, get less historical information. To solve the above problems, this paper puts forward based on improved LSTM (long short-term memory) modeling method of network model. The model increases the connection from the current input gate to the output gate, and simultaneously combines the oblivious gate and the input gate into a single update. The door keeper input and forgotten past and present memory consolidation, can choose to forget before the accumulation of information, the improved LSTM model can learn the long history of information, solve the drawback of the LSTM method is morerobust. This paper uses the neural network languag LSTM model based on the inproved model on TIMIT data sets show that the axxuracy of test. The results illustrate that the improved LSTM identification error rate is 5
% lower than the standard LSTM identification error rate.

6216| 3134

Analysis on Ultimate Bearing Capacity of Ground Foundation Adjacent to Slope Based on Bilateral Asymmetry Failure Mode[85-91]

Jiang Yang1,Guo Jiankun 1，Wang Xiaomou 2，Hou Chaoqun 3

Doi:10.13705/j.issn.1671-6833.2018.06.016

Abstract: In the field of engineering construction, foundations were often placed adjacent to slopes. In the present research work, the evaluation of the maximum bearing capacity of slope foundations lacked a sufficientrate method. A bilateral asymmetry slip failure model for ground foundation adjacent to slope was develthe strength of soil on the side of flat ground was reduced and this is characterized by a mobilization factor. Base on limit equilibrium method and superposition principle, three bearing capacity factors were ex-pressed. The upper bound bearing capacity for ground foundation adjacent to slope was deduced based on limitanalysis approach. Centrifugal model tests were used to verify the theoretical analysis results; and thetion and failure characteristics of these foundations were studied. In addition the influence of variousuch as the contact conditions of the foundation, the location of the foundation, and the height of slope on themaximum bearing capacity of these foundation

6173| 3312

Study on Numerical Simulation of The Steam Turbine Blade Aerodynamic steam turbine increases.Performance Optimization Based on ANSYS CFX[1-6]

Zhou Junjie, Wang Pu, Zhou Jinfang

Doi:10.13705/j.issn.1671-6833.2017.01.008

Abstract: The analysis was held with the 125MW axial flow steam turbine impulse stage blade.The three-dimensional numerical simulation and optimization were conducted by using the commercial software ANSYS CFX.The results showed that the pressure distribution of blade surface reduced,and the radial secondary flow loses was controlled effectively,with optimizing the structure geometric parameters such as ellipticity of the leading edge and trailing edge,relative pitch,inter-stage ratio,and so on.Isentropic efficiency increased by 0.43％,the total pressure loss coefficiency decreased about 0.005.After the optimization,the aerodynamic performance of the blade increased,and the energy loss in the blade decreased and the efficiency of steam turbine increased.

6111| 3935

Review on Modeling and Control of Proton Exchange Membrane Fuel Cell[61]

Han Chuang, Wu Lili

Doi:10.3969/j.issn.1671-6833.2015.06.012

Abstract: For the modeling and control of proton exchange membrane fuel cells, the empirical model and mechanism model based on polarization curve and parameter dimension are summarized, the electrochemical steady-state model and dynamic model based on electrochemical reaction, temperature, pressure and other factors are analyzed, and the intelligent method model based on neural network identification, swarm intelligence algorithm and support vector machine is introduced.The existing intelligent control strategies of proton exchange membrane fuel cells are summarized. Finally, it is pointed out that it will be a development direction of modeling to optimize the model parameters and environmental parameters of proton exchange membrane fuel cells by using swarm intelligence algorithm. The generalized Hamilton theory can also be tried to be used in the modeling of proton exchange membrane fuel cells.At the same time, the intelligent control strategy combining the new algorithm will become the research trend of proton exchange membrane fuel cell control.

6083| 5055

Preparation of Zirconium Oxide / Graphene Composites and their Adsorption Properties for PO43-[23-28]

Shi Chunyan1,Fan Bingbing1,Li Yaya1,Hu Yongbao1,Zhang Rui2

Doi:10.13705/j.issn.1671-6833.2017.01.009

Abstract: In this work,graphene oxide (GO) was prepared by an improved Hummers method.Zirconia/graphene composites (ZrO2/rGO) were rapidly synthesized by hydrothermal method with Zr(OH)4/rGO as precursor prepared by ultrasound-stirred-coprecipitation.The adsorption capacity of Zr (OH) 4/rGO and ZrO2/rGO composites decreased with the increase of pH value and increased with the increase of phosphate concentration and the solution temperature.The maximum adsorption capacities of Zr (OH)4/rGO and ZrO2/rGO composites were 81.84 mg/g and 63.58 mg/g respectively at pH 2.0.The adsorption kinetics of these two adsorbents accorded with the pseudo-second-order model and isothermal adsorption complied with the Langmuir isotherm equation.The results of its recycling properties showed the adsorption capacity decreased for the Zr (OH) 4/rGO samples,while ZrO2/rGO samples were almost the same as the initial adsorption performance.

6056| 4202

Preparation and applications of molybdenum disulfide nanoplate based nanocomposites[18]

CHEN Deliang,DONG Huina,ZHANG Rui

Doi:10.3969/j.issn.1671-6833.2015.06.005

Abstract: Molybdenum disulfide ( MoS2 ) with a typical layered structure easily forms few-layered MoS2 nanosheets，and has a wealth of optical，electrical and catalytic performance with wide application potentials in areas such as photo-electrical and energy conversion． The preparation of few-layered MoS2 nanocrystals and MoS2-based nanocomposites using molybdenum-containing chemicals as starting materials by wet-chemical and vapor-deposition methods are the cutting-edge focuses of recent research． However，the synthesis of MoS2 nanocrystals from chemical reagents with a long route is not low-carbon and environment friendly． Molybdenite is a typical layered mineral and composed of layered MoS2 units． The amount of molybdenite in China is huge and it is a green and low-carbon way to prepare few-layered MoS2 nanomaterials via the intercalation-exfoliation strategy using the purified molybdenite as the direct raw materials．

6030| 8802

Optimized Echo State Network on the Basis of Mutual Information and Just-In-Time and its application[1-6]

Zhang Heng, Wang Heshan

Doi:10.13705/j.issn.1671-6833.2017.05.018

Abstract: To improve the adaptability of echo state network (ESN),an optimization method based on mutual information (MI) and Just-In-Time (JIT) learning was proposed in this paper to optimize the input scaling and the output layer of ESN.The method was named as MI-JIT optimization method and the obtained new network was MI-JIT-ESN.The optimization method mainly consists of two parts.Firstly,the scaling parameters of multiple inputs were adjusted on the basis of MI between the network inputs and outputs.Secondly,based on JIT learning,a partial model of output layer was established.The new partial model could make the regression results more accurate.Further,a multi-input multi-output MI-JIT-ESN model was developed for the fed-batch penicillin fermentation process.The experimental results showed that the obtained MI-JIT-ESN model performed well,and that it had better adaptability than ESN model without optimization and other neural network models.

5987| 4184

Design of a Cooker Anti-overheating System based on Non-contact Temperature Measurement[18-22]

Li Yifeng, Mao Xiaobo, Yang Yihang, Zhu Feng

Doi:10.13705/j.issn.1671-6833.2017.05.021

Abstract: In order to prevent the serious safety problem caused by the dry pot burning and stove explosion and firing,an anti-overheating system was designed.The system of infrared temperature sensor MLX90614 on the bottom of the pot was used to realize the non-contact real-time temperature monitoring.The real-time temperature data was collected and processed by the STM32 microcontroller and SMBus.When the temperature of the bottom of the boiler was beyond the normal heating range,the temperature monitoring module could send a voice alarm.When the threshold value of the dry burning temperature was reached,the gas circuit could be cut off by the control circuit serially connected in the thermocouple temperature detection circuit.Experimental results showed that the proposed system could cut off the gas path once the preset temperature reached and prevent the dry pot burning effectively.

5870| 5180

Moth-flame Optimization Algorithm Based on Chaotic Initialization and Gaussian Mutation[53]

Liu Qian; Feng Yanhong; Chen Yingying;

Doi:10.13705/j.issn.1671-6833.2021.03.009

Abstract: Moth-flame optimization algorithm (MFO) has some drawbacks in solving optimization problems, such as low precision and high possibility of being trapped in local optimum. A modified MFO algorithm based on chaotic initialization and Gaussian mutation is proposed. Firstly, the cube chaotic map is used to initialize the moth population, which makes the moth more evenly distributed in the search space. Then, Gaussian mutation is adopted to disturb a few poor individuals to enhance the ability of escaping the local optimum. Finally, Archimedes curve is introduced to expand the search scope and strength the exploration ability in the unknown field. A series of experiments are carried out on CEC14 test function set and 21 extensible Benchmark functions. Compared with standard moth-flame optimization algorithm, genetic algorithm, artificial bee colony algorithm, particle swarm algorithm, differential evolution algorithm, flower pollination algorithm, and butterfly optimization algorithm, the results demonstrate that the proposed algorithm is strengthened in obtaining solutions with better quality and convergence.

5860| 1163

System for automatic recognition and renewal of driving license[13-17,22]

Maling1,Jiang Huiqin1,Liu Yumin2

Doi:10.13705/j.issn.1671-6833.2017.05.013

Abstract: In order to meet the practical requirements of automatic application and renewal of driver’s license,a high speed system for automatic recognition of driver’s licenser was designed and implemented.The hardware was designed to capture the image of the driver’s license that contained the smallest identifiable features.Because of the complex background such as the shadow line and so on in the driver’s license images,the existing recognition algorithms had the low recognition accuracy,universality and robustness problems.This paper first solved the segmentation difficulties for uneven illumination,noise,tilt and shadow line character by combined adaptive binarization and morphological processing.Then,the Blob analysis was used to extract the important local features of the driver’s license,and the recognition accuracy was further improved by using the prior information and the correlation matching algorithm.The experimental results showed that not only the false recognition rate was 0,but also the practical products was developed,and the better social effects were achieved.

5839| 3926

Probabilistic Conditional Preference Network Assisted Interactive Genetic Algorithm and Its Application[1-5]

Sun Xiaoyan, Zhu Lixia, Chen Yang

Doi:10.13705/j.issn.1671-6833.2017.06.001

Abstract: Interactive evolutionary algorithms with user preference implicitly extracted from interactions of user are more powerful in alleviating user fatigue and improving the exploration in personalized search or recommendation. However, the uncertainties existing in user interactions and preferences have not been considered in the previous research, which will greatly impact the reliability of the extracted preference model, as well as the effective exploration of the evolution with that model. Therefore, an interactive genetic algorithm with probabilistic conditional preference networks (PCP-nets)is proposed , in which, the uncertainties are further figured out according to the interactions, and a PCP-net is designed to depict user preference model with higher accuracy by involving those uncertainties. First, the interaction time is adopted to mathematically describe the relationship between the interactions and user preference, and the reliability of the interaction time is further defined to reflect the interactive uncertainty.The preference function with evaluation uncertainty is established with the reliability of interaction time. Second, the preference weights on each interacted object are assigned on the basis of preference function and reliability. With these weights, the PCP-nets are designed and updated by involving the uncertainties into the preference model to improve the approximation. Third, a more accurate fitness function is delivered to assign fitness for the individuals. Last, the proposed algorithm is applied to a personalized book search and its superiority in exploration and feasibility is experimentally demonstrated.

5815| 4460

Research on control of permanent magnet synchronous linear motor based on energy forming[1-5]

JIAO Liu-cheng,YAO Tao

Doi:10.3969/j.issn.1671-6833.2015.03.001

Abstract: In view of the speed control problem of the linear permanent magnet synchronous motor ( L.PMSM) ,which is viewed as an energy-transformation device,from the viewpoint of energy shaping,applying port-con-trolled Hamultonian with dissipation and passivty-based control theory,the port-controlled Hamltonan modelof LPMSM is deduced. Based on the Hamiltonian structure,the desired Hamiltonian function of the closed-loop system is given,and the speed controller is designed by using the method of interconnection and dampingassignment. In the design,the Hamiltonian function is used directly as the storage function,and the systemcan achieve the required performance and bring more definite physical meaning on the condition of satisfyingpassivity. The simulation results show that the closed-loop control system can respond quickly to changes inload resistance and has good robustness.

5792| 3964

A Survey of Evolutionary Algorithms for Large Scale Optimization Problem[15-21]

Liang Jing1,Liu Rui1,Qu Boyang2,Yue Caitong1

Doi:10.13705/j.issn.1671-6833.2017.06.016

Abstract: Based on the characterisities of large-scale problems, lager-scale optimization were grossly analyzed. This paper introduced some methods for lager-scale problems.The methods included the initialization method, decomposition strategy, updating strategy and so on. This paper mainly focued on the search strategy, update strategy, mutation strategy and cooperative coevolution. Meanwhile, the characteristics of lager-scale optimization algorithm testing function set and evaluation method were listed. Finally, the future research directions were given.

5792| 4442

The Haze Plate Recognition System Based on PSO-RBF Neural Network[46-50]

Mao Xiaobo, Zhang Qun,Liang Jing, Liu Yanhong

Doi:10.3969/j.issn.1671-6833.2017.04.002

Abstract: In this paper,a new algorithm of license plate recognition in the hazy weather was designed.Firstly,defogging operation was introduced for license plate image in the environment of hazy by using improved dark channel prior.Then after the pretreatment,positioning,segmentation and extraction,coarse grid characteristic matrix is obtained.Finally,radial basis function (RBF) neural network,which was optimized by particle swarm algorithm in advance,was used to identify the character.The experiment results showed that the improved algorithm not only had a good effect on haze removal,but also reduced the duration of defogging,which effectively improve the license plate recognition speed and accuracy in fog and haze weather.

5784| 4123

Preparation of Supported Phosphotungstic Acid Catalyst andlts Application in the Synthesis of BEA[49-53]

WAN Ya-zhen,LIU Ya-nan,CHEN Di

Doi:10.3969/j.issn.1671-6833.2015.04.012

Abstract: PTA supported catalyst was prepared by dip roasting method for the synthesis of 2-(4’ -ethyl benzoyl) benzoic acid (BEA) from phthalic anhydride and ethyl benzene as raw materials and chlorobenzene as solvent.The experimental results showed that when the load of PTA was 30%(mass fraction) and the roasting temperature was 300℃, the catalytic activity of PTA was more than doubled with SiO2 as the carrier.The effects of XRD on loading capacity and NH3-TPD on calcination temperature were analyzed. Ft-ir and BET were used to characterize PTA/SiO2 catalysts.The reuse performance of PTA/SiO2 catalyst was investigated, and the results showed that the original catalytic activity of PTA/SiO2 was still maintained after repeated use.

5780| 3740

Effect of particle diameter and particle axial distribution on heat and mass transfer inside adsorption heat transformer[17-22]

Sheng Zunrong1,Xue Bing1,Liu Zhouming1,Wei Xinli2

Doi:10.3969/j.issn.1671-6833.2017.01.011

Abstract: A direct-contact method of zeolite adsorption liquid water was adopted to enhance heat and mass transfer rate within adsorption heat transformer.Hot water was recycled to generate superheated steam directly,and then saturated zeolite would be regenerated by drying gas.The reactor with was filled spherical zeolite with same mass and different diameters.The mass of steam generated by small particle packed bed was 64.89％ higher than that generated by big particle packed bed.The maximum steam temperature and gross temperature life had increased by about 37C.Experiments of two kinds of packed types in double layer reactor (finecoarse bed and coarse-fine bed) have shown that small particle played a more effective role for the heating of steam and packed bed;the mean maximum temperature of the steam at the top of fine-coarse bed is 37.23％ higher than that of coarse-fine bed and the lasting time of the maximum temperature is decreased by 14.25％.The steam generation rate of fine-coarse bed was 16.18％ higher than that of coarse-fine bed,which is more efficient in steam generation.In regeneration process,drying time of upper reactor was 25.03％ shorter than coarse-fine bed.It concluded that fine-coarse bed was more effective for zeolite regeneration.

5759| 4059

The filtration method of cliff point cloud vegetation based on the surface orthographic projection[77-82]

Li Cailin, Chen Wenhe, Wang Jiangmei, Tian Pengyan, Yao Jili

Doi:10.13705/j.issn.1671-6833.2016.06.005

Abstract: Cliff and steep slope are important landscape elements of topographic map, and these elements play a very important role in the construction of the ecological environment and prevention of geological disasters, etc. However, it is unfavorable to observe and process data because of vegetation occlusion on cliff. In this paper, we present a cliff vegetation filtration method based on the principle of surface orthographic projection. Firstly, transform the original three dimensional point cloud of cliff to the spatial cartesian coordinate system, whose xy plane is the cliff face and z-axis is perpendicular to the direction of the cliff surface. Then the grid on the xy plane is divided to establish local grid Digital Terrain Model ( DTM) by fitting surface, and the vegeta-tion points can be extracted through setting a reasonable distance threshold. Finally, after inverse projection transformation, cliff rocky points preserved are mapped to the original spatial coordinate system. The experi-mental analysis using actual cliff point cloud data shows that the cliff point cloud vegetation filtering method based on the surface orthographic projection is feasible and effective.

5755| 3656

Piles Kind Optimal and Sheet Pile Adaptability Analysis in Highway Extension Projects[44-49]

Li Haibin1,Ke Shengwang2,Shen Yanjun2

Doi:10.13705/j.issn.1671-6833.2017.05.006

Abstract: With the increasing of highway extension projects and widely use of sheet piles in railway construction,the mechanical behavior of extension embankment was analyzed through simulating different kinds of pile and load of different positions.Then the optimal pile kind and the most unfavorable load position were proposed.Through continuous observing of settlement in sheet pile section and CFG pile section,the optimal adaptability of sheet pile was showed in extension projects.The analysis results showed that the effect on settlement of PTC pile,CFG pile and cement mixing pile was gradually decreased.The PTC pile and CFG pile should be firstly selected from the options of controlling settlement.The most unfavorable load position was in new embankment and its quality was the key control point in construction.The effect on decreasing differential settlement was appeared in process of semi-rigid base construction,and it would be even obvious in pavement construction.The sheet pile was an effective supplement to traditional soft soil treatment methods.It had better adaptability and foreground in highway extension projects.

5750| 3849

Electric field analysis in electrospinning based on COMSOL Multiphysics[46]

LIU Zhenghua1, WANG Jing2,DU Haiying’1,2

Doi:10.13705/j.issn.1671-6833.2016.03.010

Abstract: In order to solve the problem that electrospinning process is hard to control，FEA tool softwareCOMSOL Multiphysics was used to simulate the the electric field orientation within the electrospinning. Basedon the vector maps and contour lines, the electric fields distribution was analyzed. Which includes single-nee-dle electrospinning device，electrospinning device with circle and orparallel auxiliary electrodes. Experimentwith parallel auxiliary electrodes was conducted，and the deposition area with the ellipse shape matched thesimulation result.

5719| 3359

Application of Information Fusion in Welding based on Arc and Ultrasonic sensor[28-31,38]

Liu Guangrui; Zhou Wenbo; Tian Xin; Guo Kefu

Doi:10.13705/j.issn.1671-6833.2017.02.025

Abstract: BP neural network for effectively fusioning the information obtained by arc sensor and ultrasonic sensor and information of welding parameters such as welding current,welding speed,welding groove and so on was used to obtain the prediction model of weld penetration depth.Simulation results showed that:the prediction model of weld penetration depth could measure the weld penetration quickly,accurately and in real time.For the precise control of weld penetration,parameters self-tuning fuzzy PID controller was desing,which combined with the advantages of traditional PID controller and fuzzy controller.Smulation results showed that compared with traditional PID controller,parameters self-tuning fuzzy PID controller had a significant advantage in the performance of the system.

5690| 4227

The Analysis and Improved Design of a New AGV Drive Unit Based on Differential Driving[73-78]

Zhao Huadong, Jiangnan, Lei Chaofan

Doi:10.13705/j.issn.1671-6833.2018.05.012

Abstract: Commercial automayic guided vehicles (AGV) usually used chain transmission mechanism power transmission, and the fixed structure of the wheel could be considered as cantilever structure. Therefore, the problem of wheels "tilting" and start-stop "shocking" easily occurs, which limited the accurate movement of the AGV during frequent and rapid acceleration or deceleration. In this paper, AGV designed by a company was taken as an example. Though repeated tests and numerical simulations, the structure and force analysis were used to find out the reasons for this phenomeno. The larger stress was caused by the "L"-shaped suspension mechanism, which magnified the contact gaps of each component; the uses of the chain transmission mechanism could make it easy for the AGV to form gaps between the sprocket and the chain when the AGV started, stopped, moved forward, backward frequently. Then a new drive unit structure was put forward from the engineering point of view, which could solves the above problems, at the same time-greatly could reduced the stress in the mechanism, could improve the transmission precision, and could provide a more practical and optimized driving structure for the design of AGV.

5670| 3323

Algorithm of Target Tracking Based on Mean Shift with ELM[1-5]

Mao Xiaobo, Hao Xiangdong, Liang Jing

Doi:10.3969/j.issn.1671-6833.201503043

Abstract: In view of the problem of object deviation when occlusions occur during the target tracking, a new algorithm using Mean Shift with ELM is proposed. According to the formal information of the object’ s loca-tion, current possible location was predicted by ELM, the iteration was started from the possible location in-stead of formal location, and the object’ s real center is calculated by mean shift algorithm. The simulation re-sults show that proposed algorithm can track precisely target occluded, operation time and number of iteration are reduced so that efficiency and robustness are improved.

5660| 4066

Effects Evaluation of the Impact on Carbon Emission Intensity by Consumption of Main Types of Energy in China Based on LSDV Estimation[90-94]

Wei Ran

Doi:10.13705/j.issn.1671-6833.2019.02.010

Abstract: Impact effects on carbon emissions intensity by population, per capita GDP, and main types of energy in China were evaluated with the fixed effect model based on LSDV estimation with reasons of the results of Likelihood Ratio Test and Hausman Test. The traditional model of STIRPAT was improved by adding Carbon Emission Intensity and Energy Consumption Variables, which included consumptions of coal, coke, crude oil, gasoline, kerosene, diesel oil, fuel oil, and natural gas, except population and per capita GDP. The results show that consumptions of different types of energy have different impacts on carbon emissions intensity from 2004 to 2016 in China. Five variables of energy consumption, which were corresponding to coal, coke, gasoline, diesel oil, and natural gas, had played positive effects on carbon emission intensity from the data of China Statistical Yearbook and China Energy Statistical Yearbook of 200 5 to 201 7. Other variables of crude oil consumption, fuel oil consumption, and kerosene consumption took opposite impact on carbon emission intensity. Moreover, change of population had the most significant favorable influence on carbon emission intensity in all studied variables. Unfortunately, per capita GDP and coal consumption contributed to the increasing of carbon emission intensity in China in the studied period.

5629| 2376

Normalized PCA Algorithm Based on Spark[7-12]

Dong Chee-hwa1,Wang Guoyin2,Yongxi3,Shi Xiaoyu2,Li Qingliang4

Doi:10.13705/j.issn.1671-6833.2017.05.001

Abstract: Principal Component Analysis (PCA) is a well known model for dimensionality reduction in data mining,it transforms the original variables into a few comprehensive indices.In this paper,we study the principle of PCA,the distributed architecture of Spark and PCA algorithm of distributed matrix from spark’s ML-lib,then improved the design and present a new algorithm named SNPCA (Spark’s Normalized Principal Component Analysis),this SNPCA algorithm computes principal components together with data normalization process.We carried out benchmarking on multicore CPUs and the results demonstrate the effectiveness of SNPCA.

5628| 4789

Maximum Power Point Tracking of Permanent Magnet Direct Drive Wind Power System Based on Sliding Mode Controller[1-5]

Liu Yanhong, Zhao Jinglong

Doi:10.13705/j.issn.1671-6833.2016.04.001

Abstract: A high-order non-singular terminal sliding mode control strategy is proposed to address the issue of achieving maximum wind energy capture in permanent magnet direct drive wind power generation systems. Based on the nonlinear model of the permanent magnet direct drive wind power generation system, a maximum power point tracking method based on optimal torque tracking is proposed, Applying high-order non-singular terminal sliding mode control to the design of torque controller and current controller for permanent magnet synchronous generator (PMSG), achieving fast tracking and stable control of the maximum power point of the permanent magnet direct drive wind power generation system without wind speed sensors. Simulation results verify the effectiveness of the proposed control scheme

5615| 3618

Sintering Furnace System Identification Based on Particle Swarm Algorithm and Neural Network Control[39-43]

Cao Ben, Yuan Zhong, Yu Liu Hong

Doi:10.13705/j.issn.1671-6833.2017.02.022

Abstract: During heating process of sintering furnace,the model parameters were easy to change,and traditional PID control was difficult to achieve the desired control effect.This paper used particle swarm optimization algorithm to identify the mathematical model of sintering furnace,for sintering furnace with high inertia,time-variation and strong time delay etc,a method of supervision and control based on RBF neural network,which combined PID control with neural network control.When temperature or parameters changed greatly,PID control played a major role.neural network played a regulatory role and compensated the shortage of PID control.The simulation results of MATLAB software showed that this method could improve the control precision of sintering furnace,which had a certain practicality.

5612| 3976

Improved AFSA Optimization of SVM in The Application of Magnetic EAS Acoustic Signal Detection[35-38,83]

Deng Jicai, Geng Yanan

Doi:10.13705/j.issn.1671-6833.2017.04.001

Abstract: In order to improve the detection rate of the acoustic magnetic EAS system,and enhance the antiinterference performance,the paper studied a new label detection algorithm that was the combination of the improved artificial fish swarm algorithm (IAFSA) and the support vector machine (SVM).An improved scheme was proposed after analyzing the strengths and weaknesses of the traditional AFSA and SVM.The experimentalresults showed that the IASFA had the faster rate of convergence and the higher accuracy than AFSA,the genetic algorithm and the particle swarm algorithm;The IASFA-SVM had the higher detection rate,the longer detective distance and the lower rate of false than the traditional magnetic label detection algorithm,and the IASFA-SVM also could meet the requirements of real-time detection.

5603| 3298

Multi-objective Evolutionary Algorithm and Its Application in Electric Power Environment Economic Dispatch[1-9]

Xiao Junming, Zhou Qian, Qu Boyang, Wei Xuehui

Doi:Multi-objective Evolutionary Algorithm and Its Ap

Abstract: The energy supply of power system is very important to modern society, and the scientific and effective solution to the problem of environmental economic dispatch of power system is the guarantee of energy supply. The multi-objective evolutionary algorithm has unique advantages in solving the problem of environmental economic dispatch of power system. This paper presses In chronological order, the multi-objective evolutionary algorithm is first introduced, and then the application of the multi-objective evolutionary algorithm in the power system environmental economic dispatching problem is discussed. The direction of development is prospected.

5598| 3688

Research and Application of HHT-Based Power Load Combination Forecasting[1-5]

JIANG Jian-dong1 ,ZHANG Hao-jie1 ,WANG Jing2

Doi:10.3969/j.issn.1671-6833.2015.04.001

Abstract: To further improve the accuracy of power load forecasting，on the basis of the analysis of affectingfactors of power load, a combination prediction model based on HHT is proposed. This model uses EMD algo-rithm to decompose the original load sequence. Thus， a stationary sequence of different frequencies，which ismore predictable than the original load sequence，can be obtained. Based on the components of different fre-quencies，according to the characteristics of the different frequency of subsequence ，the RBF neural network ,BP neural network and time series model are selected to forecast while considering the influence of temperatureon the load. Then，a new combined model can be achieved. The experiment shows that the proposed modelcan effectively improve the accuracy of load forecasting.

5568| 4295

Effects of nano-ZrO2 powder addition on properties, phase composition and microstructure of Al-Si incorporated Al2O3-C materials[15]

LIU Zhi-fang,LIU Xin-hong,HUANG Ya-lei,MA Teng

Doi:10.3969/j.issn.1671-6833.2015.05.004

Abstract: The effects of nano-ZR02 powder on the properties, composition and structure of Al-Si composite Al203-C were studied by using plate corundum aggregate and fine powder, Al powder, Si powder, graphite and nano-Zro2 powder as raw materials and phenolic resin as binder.The results show that the introduction of nano-ZRO2 powder has little effect on the strength of the sample at room temperature and high temperature, but it is beneficial to improve the molding density and oxidation resistance of the sample, and can significantly improve the thermal shock resistance of the sample.The reason for the increase of sample density is that the nano-cobalt oxide has a good filling effect and helps sintering.Nano-zro2 can promote the reaction of Al and Si to generate more non-oxide whiskers, and form a cross-linked network structure in the sample, and the toughening of nano-powder and the phase transition toughening of ZrO2 are conducive to improving the thermal shock resistance of the sample.

5567| 3100

Biodegradation of Toluene in a Biofilter under Low Concentration[12-16]

ZHU Yazhong，LI Shunyi，LUO Yimeng ，MA Hongye，WANG Yan

Doi:10.13705/j.issn.1671-6833.2017.01.010

Abstract: Self-made biological fillers embedded with Pseudomonas putida were used as biofilter packing materials for treating toluene.The effects of inlet loading rate (ILR) and empty bed residence time (EBRT) were evaluated.Changes in micro-organisms before and after the shut down period and its effect on biofilter performance were investigated.Results indicated that,no need for hanging film,activities of micro-organisms were high,capacity to eliminate toluene was strong.Optimal EBRT was 74.2 s,and removal efficiency ranged from 49.3 to 97.3 ％;maximum elimination capacity,16.97 g · (m3 · h)-1 was occurred at ILR of 22.11 g · (m3 · h)-1.The recovery time needed for achieving constant state,after biofilter shut down for 3 d,7 d and 30 d,were 5,21 and 45 h,respectively.Microbial counts after recovery were significantly higher than the 30d shut-down period,and lower layer had the highest microbial population.

5548| 3626

Experimental Study on Low Compression Ratio Screw Extruder of Straw[1]

FANGShuqi1,2,HELiping1,ZHANGLonglong1,CHANGChun1,2,BAI Jing1,2,CHENJunying1，

Doi:10.3969/j.issn.1671-6833.2015.06.001

Abstract: The effects of processing variables,such as screw speed,initial moisture content and the length ofthe straw plug pipe of extrusion process on the dewatering rate,handling capacity,output per kW h etc.were experimentally studied using a low CR screw straw extruder. And the response surface optimization exper-imental results showed the extruder can run efficiently,stably and continuously with considerate dewateringrate,handling capacity and output per kW ·h under the conditions that moisture content is 85% ,screw speed50.8 r/min,length of the straw plug pipe is 26.91 mm.

5543| 4507

Impact of Triangle Leakage on Comprehensive Performanceof Heat Exchangers with Helical Baffles[1-4]

LIU Min-shan，XU Wei-feng ，JIN Zun-long，WANG Yong-qing，WANG Dan

Doi:10.3969/j.issn.1671-6833.2014.06.001

Abstract: A numerical simulation of trisection-ellipse heat exchangers with helical baffles is carried out， andthe helix angles are 15° and 20° respectively ， and we studied the impact of triangle leakage between continu-ously overlapped and adjacent baffles on heat transfer and resistance performance of heat exchangers.Throughthe comparative analysis about the simulation results of existing triangle leakage and that of blocking trianglearea without leakage , the results show :triangle leakage makes a more serious short circuit flow for the shell-si-ded fluid;Triangle leakage makes heat transfer coefficient，shell-sided pressure drop and comprehensive per-formance of heat exchanger reduce. When triangle leakage is blocked，heat transfer coefficient increases by8.5% ~ 11% , shell-sided pressure drop increases marginally , comprehensive performance increases by 8.1 %~11 . 1 % .

5513| 3937

Hydrothermal Synthesis of CuO Micro/Nanoparticles and Their Application in Gas Sensors[10-14]

Hu Xiaobing, Xie Zhenfang, Xie Ji, Xie Lili, Zhu Zhigang

Doi:10.13705/j.issn.1671-6833.2016.03.022

Abstract: Micro/Nano-particles of CuO were prepared with hexamethylenetetramine template. The composi-tion and morphology of the product were characterized by SEM and X-ray diffraction. The synthetic powder was prepared as sensitive membrane, and its gas sensitivity was studied with a static gas distribution method. The results indicated that the uniform copper oxide powders was synthesized at the 110℃, and the molar ratio be-tween copper nitrate and hexamethylenetetramine was 1∶45. The spindle structure was around 1~2 μm, and was composed of 100 nm nanoplates. The sensor had better selectivity with CH3 COCH3 and H2 S. Copper ox-ide showed good selectivity to hydrogen sulfide and its sensitivity had a certain degree of improvement after fur-ther doping 0. 25% ~1. 25% noble metal catalyst Pt.

5500| 3843

A Distributed Clustering Mechanism Based on Energy Balancein Wireless Sensor Networks[6-10]

FENG Dong-qing,XING Kai-li

Doi:10.3969/j.issn.1671-6833.2015.03.002

Abstract: Focusing on the target tracking problem in resource-constrained wireless sensor networks,a novelenergy-balanced optimal distributed clustering mechanism is adopted by introducing an energy-balanced indexbased on the standard deviation of residual energv of nodes. Then,it is transformed into a multi-obijective con-strained optimization problem,and a binary particle swarm optimization algorithm is employed to solve thisproblem. Simulation results in Matlab environment show that the energy-balanced optimal distributed clustering mechanism guarantees energy balance and tracking accuracy comparing with the clustering mechanisms respec-tively based on the energy consumption and the extended Kalman filter,and that it improves the network life-time of nearly 2-fold,effectively prolonging the network lifetime.

5473| 3078

The HoMM-UKF Algorithm of SINS’ Attitude Estimation Model[39-45]

Ding Guoqiang1Zhang Duo1Xiong Ming1Zhou Weidong2

Doi:10.13705/j.issn.1671-6833.2017.01.017

Abstract: In order to improve the precision requirement about the attitude control of the strap-down inertial navigation system,the high order moment matching UKF (Higher-order Moment Matching UKF,HoMMUKF) algorithm was proposed,that is to estimate the SINS’ attitude parameters of based on its quaternion error model.In the recursive calculation process,for accurately approximating computational purposes,it uses high order moment matching method to calculate the average skewness value and peak value of the predicted sampling points set and their weights of the system state parameters in the view of the probability distribution.Making use of attitude quaternion method,then onlinear quaternion error model was constructed,in which model the systemnoise vector depends on system state vector,meanwhile construct its measure equation whose measurement noise vector depends on quaternion measurement vector by pseudo observation vector method was constructed,the weighted average of estimated quaternion with Lagrangian operator was calculated,the system noise variance calculation with the system noise separation algorithm was carried out,and finallyconstruct the SINS’ attitude estimation HoMM-UKF algorithms simulation on SINS attitude experiment platform was designed.It can be seen that HoMM-UKF algorithm’s calculation accuracy is higher than others and has better numerical stability,comparison of the UKF,and CDKF algorithms,and so the HoMM-UKF algorithm’s feasibility and calculation accuracy is verified.

5470| 3574

The Influence of Different Combinations of Baffles on Liquid Sloshing Under the Condition of Longitudinal Excitation[7-11,34]

Ding Chang, Fu Yantang, Wu Xuehong, Gong Yi

Doi:10.13705/j.issn.1671-6833.2017.01.012

Abstract: FLUENT software was adopted to simulate the sloshing process of liquid in container under the sudden braking condition based on VOF (volume of fluid) model.The pressure variation of front and back head was compared,which showed that the sloshing liquid mainly had a greater impact on the front head.Baffles could effectively weaken the sloshing in the container,reduce the impact on the head and improve the container safety.The liquid impact on front head was studied in the condition of different filling ratio for different baffle arrangement(all down,all up,up and downinterlaced,left and right interlaced) of five same arc baffles.Results show that the arrangement style of left and fight interlaced 、all down could reduce impact load on front head for low filling ratio,however the arrangement style of up and downinterlaced all up had poor anti-wave effect.The anti-wave effect of the arrangement style of left and right interlaced became poorer and poorer with the increment of filling ratio.Compared with other arrangement style,the arrangement style of all down had better anti-wave effect.

5428| 3722

Research on Hybrid Face Recognition Algorithm Based on Voting Extreme Learning Machine[37-41]

Chen Tiejun, Cai Jinshou, Guo Li

Doi:10.3969/j.issn.1671-6833.201505016

Abstract: Aiming at the defect that wavelet analysis cannot make full use of the unique geometric features of the data itself when dealing with multi-dimensional graphics, the second generation of curvelet transform (SGCT) method is used to process face images, and the image with the largest standard deviation is selected. Scale layer coefficients are used to complete the feature extraction of face images, and combined with data dimensionality reduction based on bidirectional two-dimensional principal component analysis (B2DPCA), a hybrid voting mechanism-based extreme learning machine (voting Extreme learning machine, VELM) face recognition algorithm. By comparing with the classification results of other algorithms, it is proved that the algorithm has a higher recognition accuracy.

5390| 3808

Research on performance improvement of crowdsourcing based on task pricing[15]

Deng Shaohong 1,Li Ling 1Guibin 2

Doi:10.13705/j.issn.1671-6833.2019.04.019

Abstract: First, according to the theory of space crowdsourcing, the concept of equivalent task representative points is proposed, and the relationship between the original task pricing law and task density, membership density, member average credibility and nearest neighbor reach distance is studied. On this basis, from the perspectives of the contractor, the platform and the contractor, According to the four steps of completing the task, a task pricing model based on multi-objective programming , a member dynamic grab order model, a task allocation model and a task completion probability prediction model are respectively established. Furthermore, the TOPSIS method is used to calculate the comprehensive evaluation index of different pricing schemes, and then choose the optimal task pricing scheme by the ranking result of the comprehensive evaluation index. Finally, the optimized scheme is compared with the original scheme. Under the condition that the total cost of the contractor is as low as possible, the platform task completion rate, the average individual member income and the unit reputation value conversion rewards are significantly improved, that is, the crowdsourcing performance are improved. The result verifies the feasibility and effectiveness of the model and provides reference for the task pricing of the crowdsourcing platform

5387| 2981

Table of Contents-Cover -Back Cover[0]

Abstract:

5385| 3310

Analysis of the Influence of Soil Electrical Parameters Frequency-dependence Characteristics on the Effective Length of the Grounding Electrode[29-34]

Li Jingli, He Pengwei, Qiu Zaisen, Li Yuanbo, Guo Liying

Doi:10.13705/j.issn.1671-6833.2017.01.016

Abstract: Impulse charactersitic of grounding devices was the important factor of lightning withstand level and lightning trip-out rate of transmission line.Based on HIFREQ program and FFTSES program in grounding power system analysis software CDEGS,this paper presented a grounding system impulse characteristic modeling considered soil frequency-dependence,especially,the Visacro-Alipio soil frequency-dependence formula has been introduced.The impact of the soil frequency-dependence on the effective length of the grounding device in different initial soil resistivity and different impulse current waveform was analyzed.The calculating results showed that when considering soil frequency-dependence,the impulse effective length would be shorter,especially for the grounding devices buried in high resistivity soil.

5337| 4609

Effect of material formulation and formed time on the morphology of Poly (vinyl alcohol)/chitosan composite fiber[1-5]

Dai Pinqiang1,Song Lairui2,Cui Zhixiang3,Wang Qianting3

Doi:10.13705/j.issn.1671-6833.2016.03.023

Abstract: Chitosan ( CS)/poly ( vinyl alcohol) ( PVA) composite fibers were fabricated by electrospinning in this study. The influences of material formulation and formed time on the viscosity,electrical conductivity and the morphology, average diameter, diameter distribution of CS/PVA composite fiber were investigated. The re-sults showed that, the introduction of CS could increase the viscosity,electrical conductivity of CS/PVA blend solution. And the viscosity of blend solution decreased with the increase of formed time. In addition, the more CS content was, the smaller diameter of CS/PVA composite fiber would be. The fiber-forming capacity of CS/PVA blend solution decreased dramatically as the solution formed time increased.

5332| 4157

Multi-Objective Evolutionary Algorithm Based on Decomposition for Engineering Optimization[38]

ZHANG Chunjiang1,2，TAN Kay Chen2，GAO Liang1, wU qing3

Doi:10.3969/j.issn.1671-6833.2015.06.008

Abstract: In order for effective application of Multi-Objective Evolutionary Algorithm based on Decomposition(MOEA/D) in engineering optimization，normalization of the range of objective values is needed. A self-a-daptive s constrained Differential Evolution ( gDE) algorithm is proposed to obtain the minimum and maximumvalues of each objective on the Pareto Front ( PF). After normalization，MOEA/D can then be effectively ap-plied. In addition ,the self-adaptive s constraint method is combined with MOEA/D for constraint handling. Abenchmark problem and a weld bean design problem are used to evaluate the performance of the algorithm a-gainst two other normalization methods. One main advantage of the proposed method is the selective concen-trated optimization on some regions on the Pareto front which allows handling of problems where regions of Pa-reto front are difficult to be optimized.

5303| 5045

Scheme Study of Intelligent Planning About Distribution Network Divisional on Spectral Clustering[32-38]

Zhang Zhonghui, Liu Gushuai, Xiong Jianfeng, Liu Xiaowan, Xu Gaochao

Doi:10.13705/j.issn.1671-6833.2017.05.022

Abstract: The distribution of charging and battery swap station has always been one of the key problems for the development of electric vehicle.A site location of charging and battery swap station could be represented by a network with traffic flow,the distance from the power source,parcel load,and city block position respectively.Spectral clustering methodology was used to reveal the internal connectivity structure of such a network.First of all,it adopted the min-max standardized method in dimensionless to establish a sample space matrix S.Then,the normalized Laplacian was achived according to the similarity between matrix W and matrix D.The former two and three feature vector of Laplace matrix were mapped to the 2d and 3d space to observe parcel partition.Finally methodology goes beyond the standard k-means algorithm by instead representing the complete network substructure as a dendrogram and verifies its correctness by analyzing the voltage sags.We include the results of our methodology for a real distribution network in Jiangxi province.Example shows that our methodology has certain rationality and it could be helpful for distribution network planning.

5275| 3816

Study of Face Orientation Recognition Based on Development Network[23-27]

Wang Dongshu, Tan Dapei, Wei Xiaoqin

Doi:10.13705/j.issn.1671-6833.2017.02.023

Abstract: Based on the characteristic of face orientation,position and the light background in face recognition,a new method of face orientation recognition based on development network is proposed.The characteristic of human’s eye was very prominent,so the position of eyes was chosen as the face orientation feature vector.And the deveiopment network model was used to recognize human’s face orientation in the different light background images.The result showed that this method could effectively solve the difficult problem of face orientation recognition under varying illumination conditions by comparing with the test results of other methods,which was fast,stable and effective.The recognition rate was as high as 100％.

5264| 4128

Preparation and applications of molybdenum disulfide nanoplate based nanocomposites[18]

CHEN Deliang,DONG Huina,ZHANG Rui

Doi:10.3969/j.issn.1671-6833.2015.06.005

6030| 8802

Experimental Research on Hysteretic Behavior ofHRB500 Reinforced Concrete Piers[74-77]

RONG Xian,SONG Peng,ZHANG Jianxin,etc;

Doi:10.3969/j.issn.1671-6833.2014.06.018

Abstract: Based on the quasi-static test study of seismic performance of HRB500 reinforced concrete piers ,influence law about steel strength ，the spacing，the axial compression ratio on seismic behavior was obtainedaccording to the analysis of its failure characteristics, hysteresis curves，skeleton curves，stiffness degradationunder low eyclic loads. The results show that increasing steel strength can improve components’ bearing ca-pacity and deformation capacity obviously , stirrup ratio can not influence members’ bearing capacity and de-formation capacity ,axial compression ratio can improve components’bearing capacity , but on the other hand,it is useless to improve components’deformation capacity.

4613| 7924

Zoom Camera Self-calibration Method Based on Two Vanishing Points(PD)[91-96]

Zhao Shujun, Duan Shaoli, Zhang Xiaofang, Li Lei, Liu Xiaomin

Doi:10.13705/j.issn.1671-6833.2016.05.018

Abstract: The calibration method of the zoom camera is studied. The self-calibration method based on the two vanishing points is used to calibrate the general parameters of the zoom camera under two fixed focal lengths. By comparing with Zhang Zhengyou’s calibration method and the results of the machine vision software Halcon calibration, the results are verified. The feasibility and robustness of this method are verified. In order to better reflect the zoom characteristics of the zoom camera, a thick lens model that can more accurately describe the zoom camera is established. The author performs SIFT feature matching on the zoom image, and according to the matching point pair The linear equations are established, and the least square method is used to estimate the zoom center of the zoom image. In addition, the optical center displacement between different focal lengths is also calculated. The experimental results show that there is an obvious gap between the optical center displacement and the focal length, which shows that The thick lens model is more suitable for describing the zoom lens of the camera.

5002| 5235

Design of a Cooker Anti-overheating System based on Non-contact Temperature Measurement[18-22]

Li Yifeng, Mao Xiaobo, Yang Yihang, Zhu Feng

Doi:10.13705/j.issn.1671-6833.2017.05.021

5870| 5180

Cover - Table of Contents - Back Cover[0]

Abstract:

3871| 5100

Review on Modeling and Control of Proton Exchange Membrane Fuel Cell[61]

Han Chuang, Wu Lili

Doi:10.3969/j.issn.1671-6833.2015.06.012

6083| 5055

Multi-Objective Evolutionary Algorithm Based on Decomposition for Engineering Optimization[38]

ZHANG Chunjiang1,2，TAN Kay Chen2，GAO Liang1, wU qing3

Doi:10.3969/j.issn.1671-6833.2015.06.008

5303| 5045

The Method of Degradation Feature Extraction of Rolling Bearing Based on MEMD and Multivariate Multiscale Entropy[86-91]

Li Lingjun, Jin Bingma, Yanli Han, Jie Hao, Wang body

Doi:10.13705/j.issn.1671-6833.2018.01.004

Abstract: The method of extracting degradation features was proposed based on MEMD and MMSE to solve the problem that non-stationarity of fault signals of roller bearing and degradation condition, which was characteristic of non-ststionarity and hard to recognize. The character of MEMD was adopted to catch different scales of signals effectively during the process of multiscalization, which made complexity of different degradation condition distinguished better than other methods. Firstly, multichannel signals corresponding to various degradation condition of roller bearing were decomposed adaptively using MEMD, then, the reconstructed signals by multiscale IMF was dealt with MSE analysis. The results showed that the proposed method could efficiently evaluate the degradation trend of roller bearing by handing the experimental signals.

4651| 4970

A Multi-objective Estimation of Distribution Algorithm for the Fingertip Localization[12]

Liu Ke 1;Gong Dunwei 2

Doi:10.13705/j.issn.1671-6833.2019.04.011

Abstract: In the human-computer interaction system based on fingertip, the position of fingertip center is very important. By solving the multi-objective optimization model for the fingertip localization, several fingertip center positions can be obtained. The fingertip pixels distribute around the fingertip centers, so the optimal solution components of this optimization model have the above distribution law. Using the estimation of distribution algorithm with the distribution law to solve this optimization model, can obtain accurate results. This paper discusses the estimation of distribution algorithm for the fingertip localization. It proposes that the decision variable dimension, population size, maximum sampling variance, and minimum sampling variance are the main parameters of this estimation of distribution algorithm. The experimental results show that each main parameter has its best value; when their values are their best values, the fingertip center positions obtained by the proposed method excel the results of the existing methods.

4564| 4940

A Review: Pre-warning system of oil-drilling engineering[70-73]

Li Guang1, Zhang Heng2, Wang Jie2, Zhu Xiaodong2, Yue Caitong2

Doi:10.13705/j.issn.1671-6833.2017.06.010

Abstract: Warning technology of drilling engineering was the key technolog of drilling safety protection. Through the monitoring of real-time well site drilling process parameters, huge amounts of drilling data mining and intelligent learning, abnormal state modeling and optimization, abnormal state modeling and optimization, abnormal characteristics of the early warning model online judging process, achieved the goal of oil drilling abnormal state arly warning, and prevention of drilling engineering accidents. This paper reviewed the development course of early warning technology, introduced the drilling engieering warning technology architecture, and also introduced the early warning teachnology in detail and compared their characteristics, finally depicted the development of future early warning system for drilling engineering.

5218| 4927

Research on the Method for 3D Tolerance Analysis Considering Tolerance Principle[39-44]

Zhao Fengxia , Jin Shaobo , Li Jifeng

Doi:10.13705/j.issn.1671-6833.2017.06.007

Abstract: A method of considering tolerance principle for three dimensional tolerance analysis was put forward. Based on small displacement torsor (SDT) theory and modal interval arithmetic, the tolerance models of size tolerance and geometrical tolerance of the feature of size apply independent principle, envelope requirement, maximum material requirement, least material requirement or reciprocity requirement, were established respectively. By using the space vector to represent 3D dimension chain, a mathematical model is built to calculate the closed loop tolerance based on space vector loop stack principle. The application of the proposed method is illustrated through presenting an example, the tolerance analysis steps are given, and the availability of the proposed method was proved successfully.

5175| 4842

Comparative Study on Cooling Channel for Electric Vehicle Drive Motor Based on CFD[41-45]

Shen Chao1,Yu Peng1,Yang Jianzhong1,Zhang Dongwei2,Wei Xinli2

Doi:10.13705/j.issn.1671-6833.2018.01.003

Abstract: Based on the cooling characteristics of the electric vehicle drive motor, a novel cooling structure the circumferential multi spiral structure, was proposed. The three dimensional numerical model of fluid flow and heat transfer in the shell was established. The flow field and temperature field of different water cooling schemes were calculated based on CFD technology. The numerical results showed that the temperature uniformity and cooling performance of Circumferential "Z" structure is better than the circumferential multi spiral structure; and the circumferential "Z" structure was suitable for the cooling of 135KW electric vehicle drive motor under the condition of inlet water temperature was 65ºC, with the optimal water flow rate 9.8L/min. However, the circumferential multi spiral structure could be used for higher power density of the motor cooling for the better performance of pressure resistance. The research provided a theoretical basis for cooling design and optimization of the small size and high power density motor.

4812| 4831

Normalized PCA Algorithm Based on Spark[7-12]

Dong Chee-hwa1,Wang Guoyin2,Yongxi3,Shi Xiaoyu2,Li Qingliang4

Doi:10.13705/j.issn.1671-6833.2017.05.001

5628| 4789

Swarm intelligence optimization algorithm[1-2]

Cheng Shi 1,Wang Rui 2,Wu Guohua 3,Guo Yinan 4,Malembo 5,Shi Yuhui 6

Doi:10.13705/j.issn.1671-6833.2018.06.024

Abstract: The core idea of swarmintelligence (swarmintelligence) is that several simple individuals form a group, through cooperation, competition, interaction and learning mechanisms to show advanced and complex functions, in the absence of local information and models, still able to complete the solution of complex problems.The solution process is to initialize the variable randomly, and calculate the output value of the objective function after iterative solution.Swarm intelligent optimization algorithm is not dependent on gradient information, and it is not continuous and derivable to solve problems, which makes it suitable for both continuous numerical optimization and discrete combinational optimization.At the same time, the potential parallelism and distributed characteristics of swarm intelligence optimization algorithm make it have significant advantages in dealing with big data.

5128| 4769

Research on Glass Fiber Fabric Defect Detection Method Based on Blob Analysis[90]

WANG Qinghai1，ZHAO Fengxia2,Ll Jifeng2，JIN Shaobo2

Doi:10.3969/j.issn.1671-6833.2015.06.018

Abstract: In order to solve the problems，such as low efficiency，poor real-time performance and so on，in on－line detection of glass fiber fabric，a new method of fabric defect detection based on Blob analysis is proposed． Firstly，the image is smoothed by using mean filter，and the noises and the fabric textures are weakened． Then，the Otsu algorithm is used to find the best threshold to segment the image into Blob and background pixels． The shape of the Blob region is adjusted by using morphological processing． Finally，the connectivity analysis and feature extraction of the image are carried out． The number and size of the defects are obtained by using the least square fitting of the Blob region． Experimental results show that the method is simple，reliable and robust．

4955| 4699

Study on preparation and properties of epoxy asphalt for pavement of concrete bridge deck[78-81]

Cong PeiLIANG,LIU Jianfei,ZHAO Zhiqiang,etc;

Doi:10.3969/j.issn.1671-6833.2014.06.019

Abstract: Aiming at the application of epoxy asphalt in concrete bridge pavement, epoxy asphalt was prepared. The effects of different resin content on viscosity, high and low temperature properties of epoxy asphalt bond, mechanical properties, low temperature crack resistance and high temperature stability of epoxy asphalt mixture were studied.The results show that the addition of epoxy resin can improve the road performance and mechanical properties of asphalt mixture. With the increase of the addition amount, the curing reaction process of epoxy asphalt is accelerated, the high temperature performance and fatigue resistance are enhanced, the stiffness modulus is increased, the creep rate is decreased, the low temperature crack resistance is decreased, and the fatigue resistance and high temperature stability of asphalt mixture are improved.By comprehensive analysis,30% is the best dosage of epoxy resin.

4567| 4694

Analysis of the Influence of Soil Electrical Parameters Frequency-dependence Characteristics on the Effective Length of the Grounding Electrode[29-34]

Li Jingli, He Pengwei, Qiu Zaisen, Li Yuanbo, Guo Liying

Doi:10.13705/j.issn.1671-6833.2017.01.016

5337| 4609

Experimental Study on Low Compression Ratio Screw Extruder of Straw[1]

FANGShuqi1,2,HELiping1,ZHANGLonglong1,CHANGChun1,2,BAI Jing1,2,CHENJunying1，

Doi:10.3969/j.issn.1671-6833.2015.06.001

5543| 4507

Design of Fuzzy Classification System Based on Fireworks Optimization and Differential Evolution Algorithm[47]

ZHU Xiaodong,LIU Chong,GUO Yamo

Doi:10.3969/j.issn.1671-6833.2015.06.009

Abstract: A novel approach to construct accurate and interpretable fuzzy classification system based on fire-works optimization algorithm(FOA) combined with differential evolution operators is proposed.It is the firsttime to apply FOA in fuzzy modeling.The fireworks optimization algorithm is a novel swarm intelligent algo-rithm based on simulating the explosion process of fireworks,which can optimize the construction and parame-ters of fuzzy system with good convergence speed and optimization accuracy.To improve the diversity of theswarm and avoid being trapped in local optima too early ,the differential evolution is performed to further opti-mize the model at each iteration.The proposed approach is applied to the lris benchmark classification prob-lem,and the results prove its validity.

4981| 4490

Probabilistic Conditional Preference Network Assisted Interactive Genetic Algorithm and Its Application[1-5]

Sun Xiaoyan, Zhu Lixia, Chen Yang

Doi:10.13705/j.issn.1671-6833.2017.06.001

5815| 4460

The Study of Dynamic Deflection Temperature Correction of Asphalt Pavementunder Effect of Thermal-structure Coupling Field[1-5]

ZHENG Yuanxun ，YANG Peibing

Doi:10.3969/j.issn.1671-6833.2014.02.001

Abstract: In order to study the influence of asphalt pavement temperature on pavement deflection, a finite element coupling model of asphalt pavement was established considering the temperature sensitivity of road material parameters.Based on the numerical model, the variation of pavement deflection under FWD dynamic loading under different temperature conditions and the influence of temperature on the maximum deflection of asphalt pavement with different thickness are analyzed.At the same time, the influence of asphalt pavement structure and material parameters on the dynamic bending temperature correction coefficient is analyzed. Finally, the dynamic bending temperature correction coefficient of asphalt pavement is studied based on the coupling model and compared with the test results.The results show that the pavement thickness and base modulus have great influence on the temperature correction coefficient. The temperature correction coefficient of asphalt pavement deflection established based on the finite element model is in good agreement with the temperature correction coefficient established through the experimental research, and can be used as an effective supplement to the experimental research.

3846| 4453

A Survey of Evolutionary Algorithms for Large Scale Optimization Problem[15-21]

Liang Jing1,Liu Rui1,Qu Boyang2,Yue Caitong1

Doi:10.13705/j.issn.1671-6833.2017.06.016

5792| 4442

Research and Application of HHT-Based Power Load Combination Forecasting[1-5]

JIANG Jian-dong1 ,ZHANG Hao-jie1 ,WANG Jing2

Doi:10.3969/j.issn.1671-6833.2015.04.001

5568| 4295

Effects analysis of CTE on the PCC Pavement Design[6-9]

WANG Peng , FAN Lei，CUI Can

Doi:10.3969/j.issn.1671-6833.2014.02.002

Abstract: In order to research the effects of coefficient of thermal expansion ( CTE) on the PCC pavement de-sign，some efforts have been done. According to the PCC pavement design standard in our country ，the influ-ence of CTE on the temperature stress is analyzed , and the M-E design method is used to analyses the influ-ence of CTE on transverse joint faulting. The conclusion is drawn that CTE has a great impact on the designingof pavement thickness especially on the joint load transfer and the warping of slab corner. So introducing theparameter of CTE to the PCC pavement design is of great significance.

4621| 4255

Application of Information Fusion in Welding based on Arc and Ultrasonic sensor[28-31,38]

Liu Guangrui; Zhou Wenbo; Tian Xin; Guo Kefu

Doi:10.13705/j.issn.1671-6833.2017.02.025

5690| 4227

Preparation of Zirconium Oxide / Graphene Composites and their Adsorption Properties for PO43-[23-28]

Shi Chunyan1,Fan Bingbing1,Li Yaya1,Hu Yongbao1,Zhang Rui2

Doi:10.13705/j.issn.1671-6833.2017.01.009

6056| 4202

Optimized Echo State Network on the Basis of Mutual Information and Just-In-Time and its application[1-6]

Zhang Heng, Wang Heshan

Doi:10.13705/j.issn.1671-6833.2017.05.018

5987| 4184

Effect of material formulation and formed time on the morphology of Poly (vinyl alcohol)/chitosan composite fiber[1-5]

Dai Pinqiang1,Song Lairui2,Cui Zhixiang3,Wang Qianting3

Doi:10.13705/j.issn.1671-6833.2016.03.023

5332| 4157

The Morphology and Mechanical Properties of Poly(Lactic Acid) Stereocomplex Crystal[83-87]

Liu Yanping Wei Hanghang, Li Qian

Doi:10.13705/j.issn.1671-6833.2017.06.017

Abstract: The surface morphology and the different mechanical properties between crystalline region and amorphous region of the stereocomplex crystal were studied in this paper. The same mass ratio of Poly (L-lactic acid) (PLLA) and poly (D-lactic acid) (PDLA) stereocomplex was prepared by solution blending. Differential Scanning Calorimetry, Polarizing Microscope, Atomic Force Microscopy, Confocal Laser Scanning Microscope and Nano Indentation Tester were used to list the surface morpholigy of PLA stereocomplex crystal and the diversification of mechanical properties. The result showed that a high degree of stereo-tacticity of PLLA/PDLA blend could be achieved from the mass ratio of 1/1 for sample.The research also showed that obviously depression phenomenon on the surface of crystal was formed due to the contraction of the molecular chain. Furthermore, the hardness and modulus of crystalline region were improved compared to the amorphous region.

4642| 4138

A New Cryptophane A-coated SAW Methane Gas Sensor[6-23]

Wang Wen1,Hu Haoliang1,He Shitang1,Pan Yong2,Zhang Caihong3

Doi:10.13705/j.issn.1671-6833.2016.03.026

6954| 4134

Study of Face Orientation Recognition Based on Development Network[23-27]

Wang Dongshu, Tan Dapei, Wei Xiaoqin

Doi:10.13705/j.issn.1671-6833.2017.02.023

5264| 4128

The Haze Plate Recognition System Based on PSO-RBF Neural Network[46-50]

Mao Xiaobo, Zhang Qun,Liang Jing, Liu Yanhong

Doi:10.3969/j.issn.1671-6833.2017.04.002

5784| 4123

A Survey on Genetic Programming to Image Analysis[3-13]

Bi Ying,Xue Bing,Zhang Mengjie

Doi:10.13705/j.issn.1671-6833.2018.06.018

7817| 4093

Algorithm of Target Tracking Based on Mean Shift with ELM[1-5]

Mao Xiaobo, Hao Xiangdong, Liang Jing

Doi:10.3969/j.issn.1671-6833.201503043

5660| 4066

Design and Implementation of Cyberspace War Situation Visualization System for Joint Operations.[45-51]

Zhang Yang; Si Guangya; Wang Yanzheng

Doi:10.13705/j.issn.1671-6833.2018.05.004

Abstract: In this paper, the system function analysis was carried out based on the capability demand of the joint operation for Cyberspace War Situation Visualization System(CWSVS). Then, a distributed system architecture based on HLA was constructed based on the capability perspective, service perspective and operational perspective, and the scenario generating architecture and real-time running architecture were designed. The component-based rapid and customizable situation driven technology and the map-based multi-layered dynamic fusion visualization technology were taken as the key technology examples. At last, the cyberspace Offensive and defensive operations against the C4ISR system was given as an typical example, and the utility of the system was demonstrated

4992| 4061

Effect of particle diameter and particle axial distribution on heat and mass transfer inside adsorption heat transformer[17-22]

Sheng Zunrong1,Xue Bing1,Liu Zhouming1,Wei Xinli2

Doi:10.3969/j.issn.1671-6833.2017.01.011

5759| 4059

Power Load Characteristic Classification Technology Research Based on An Improved Fuzzy C-means Clustering Algorithm[56]

ZHAO Guosheng1,NIU Zhenzhen1，LIU Yongguang2, SUN Chaoliang2

Doi:10.3969/j.issn.1671-6833.2015.06.011

Abstract: In view of the disadvantages of the traditional Fuy C-means clustering algorithm， the author pro-poses an adaptive FCM algorithm. This algorithm is based on two clustering results evaluation index of withinthe class distance MIA and between the class distance MDC. The ratio of MDC and MIA，defined as l, is anadaptive function to determine the clustering number c of FCM algorithm. At the same time，according to thefuzy decision method，we use the objective function and partition entropy of FCM algorithm together to deter-mine the value of optimal fuzzy weighted m. ’This algorithm not only overcomes the FCM algorithm disadvan-tage of not being able to determine the clustering number automatically and fuzzy weighted index needs to begiven by experience,but also the clustering result is optimal. Finally,the correctness and effectiveness of thealgorithm were proved through example analysis.

4782| 4027

Design of Splitters in Flue of SCR System for a 6U Mw Coal-fired Boiler[37-40]

WANG Wei-shu1, SHAGN GUAN Shan-shan1,LU Tong1 ,YANG Zhi-feng2 ,ZHENG Chun-xiong1,CHEN Gang1

Doi:10.3969/j.issn.1671-6833.2015.04.009

Abstract: Based on FLUENT6.3 software，the simulation and analysis were applied to the optimization designof splitters in Selective Catalytic Reduction ( SCR ) denitrification system for a 600MW coal-fired boiler. Theresults show that because of variable cross-section and deflection in flue,flow field in the system appears non-uniform severely when there is no splitters. The velocity difference on two sides of the section at AlG lowerreaches is up to 15 m/s，the velocity deviations in the reactor inlet is 31.25% , and the flow field is poor intail flue，which affects the operation of downstream equipments.Reasonable splitters can improve flow field influe effectively. After equipping the transition pipe of the inlet with two group of longitudinal splitters, the ve-locity deviations in section at AIG lower reaches is reduced to 15% and in the reactor inlet is reduced to 13% .Splitters in elbow is equipped with an extension for guiding，which have a good effect on homogenization of thedownstream flow field.

5115| 3998

Sintering Furnace System Identification Based on Particle Swarm Algorithm and Neural Network Control[39-43]

Cao Ben, Yuan Zhong, Yu Liu Hong

Doi:10.13705/j.issn.1671-6833.2017.02.022

5612| 3976

Double-Buffered Queue-Based Parallel Processing Algorithmfor Massive Terrain Dataset[6]

CHEN Xiaopan1 ,QU Jiantao1,2,ZHAO Yameng2, WANG Peng1, 2 , CHEN Yulin1

Doi:10.13705/j.issn.1671-6833.2016.03.002

Abstract: When dealing with massive terrain data ，the advantage of hardware performance can’t be fully uti-lized. This has become a bottleneck，which restricts the speed of massive terrain tiles rendering. This paperanalyzes the key factors that affect large-scale terrain rendering speed，and proposes a parallel algorithm formassive terrain data processing. The algorithm adopts double buffer queues and divides large scale terrain ren-dering into two parallel processing which includes data processing and rendering. The two buffer queues areresponsible for data reading and writing operations in turn. The loading priority of terrain tiles is consideredand tasks are allocated based on the priority. The experimental results show that this approach improves thespeed of rendering massive terrain tiles greatly.

5040| 3967

Research on control of permanent magnet synchronous linear motor based on energy forming[1-5]

JIAO Liu-cheng,YAO Tao

Doi:10.3969/j.issn.1671-6833.2015.03.001

5792| 3964

Impact of Triangle Leakage on Comprehensive Performanceof Heat Exchangers with Helical Baffles[1-4]

LIU Min-shan，XU Wei-feng ，JIN Zun-long，WANG Yong-qing，WANG Dan

Doi:10.3969/j.issn.1671-6833.2014.06.001

5513| 3937

Study on Numerical Simulation of The Steam Turbine Blade Aerodynamic steam turbine increases.Performance Optimization Based on ANSYS CFX[1-6]

Zhou Junjie, Wang Pu, Zhou Jinfang

Doi:10.13705/j.issn.1671-6833.2017.01.008

6111| 3935

System for automatic recognition and renewal of driving license[13-17,22]

Maling1,Jiang Huiqin1,Liu Yumin2

Doi:10.13705/j.issn.1671-6833.2017.05.013

5839| 3926

Piles Kind Optimal and Sheet Pile Adaptability Analysis in Highway Extension Projects[44-49]

Li Haibin1,Ke Shengwang2,Shen Yanjun2

Doi:10.13705/j.issn.1671-6833.2017.05.006

5750| 3849

A contract-based cooperative spectrum sharing approach in cognitive radio system[1]

MU Xiaomin ， SHI Guangqiang，LIU Ying , YANG Shouyi

Doi:10.13705/j.issn.1671-6833.2016.03.001

Abstract: To solve the problem of contract-based cooperative spectrum sharing between multiple primary usersand multiple secondary users,we put forward a contract design method based on statistical theory to maximizethe total utility of primary users. Firstly，the primary users make full use of the accepting contract statisticalinformation of secondary users to design a reasonable contract. Then，the primary users according to the statis-tical expected utility to obtain the optimization problem of maximizing theirs total expected utilities. Further-more，we simplify the problem in theory and exploit the genetic algorithm to derive the sub-optimal solution.The simulation results and analysis show the contract design method can solve the problem of contract-basedcooperative spectrum sharing successfully.Compared with the DMA-UI,the approach we formulated can makeprimary users obtain a higher utility， and further improve the primary users’energy efficiency and spectrumefficiency.

5248| 3848

Hydrothermal Synthesis of CuO Micro/Nanoparticles and Their Application in Gas Sensors[10-14]

Hu Xiaobing, Xie Zhenfang, Xie Ji, Xie Lili, Zhu Zhigang

Doi:10.13705/j.issn.1671-6833.2016.03.022

5500| 3843

Scheme Study of Intelligent Planning About Distribution Network Divisional on Spectral Clustering[32-38]

Zhang Zhonghui, Liu Gushuai, Xiong Jianfeng, Liu Xiaowan, Xu Gaochao

Doi:10.13705/j.issn.1671-6833.2017.05.022

5275| 3816

Research on Hybrid Face Recognition Algorithm Based on Voting Extreme Learning Machine[37-41]

Chen Tiejun, Cai Jinshou, Guo Li

Doi:10.3969/j.issn.1671-6833.201505016

5390| 3808

The Optimum Selection of Electrical Equipment Types for Specialized Transmission Project Based on Improved Ant Colony Optimization Algorithm[15-19]

Jiang Yuewen, Qian Jiaqi

Doi:10.13705/j.issn.1671-6833.2016.04.004

Abstract: In response to the current construction status of specialized transmission projects, optimization methods are adopted to select the main electrical equipment of the transmission project, such as high-voltage circuit breakers, transmission lines, transformers, etc. An optimization model is established that considers one-time investment, annual operation and maintenance costs, and power outage losses. The optimization model is used to select the most cost-effective investment plan from a large number of electrical equipment that meet the technical parameter requirements. This plan takes into account both economy and reliability, To minimize the annual comprehensive operating cost, an ant colony algorithm was used to solve the problem. In response to the slow optimization speed of the algorithm, an improved neighborhood ant "benchmark" learning algorithm was used for optimization. Finally, the effectiveness of the model and algorithm was demonstrated through calculation and analysis of a residential dedicated transmission project example

4553| 3764

Journal Information

Bimonthly(Started in 1980)

Administrated by:
The Education Department of Henan Province
Sponsored by: Zhengzhou University
Edited & Published by:
Editorial Board of Journal of Zhengzhou University( Engineering Sciences)
E-mail: gxb@zzu.edu.cn
Website: http://gxb.zzu.edu.cn/
Address: No.100 Science Avenue,100,
Zhengzhou 450001,China
Telephone: (0371)67781276 67781277
Chief Editor: ZHENG Suxia
Executive Chief Editor: XIANG Sa
Printed by: Shanxi Tongfang Knowledge Network Printing Co.,Ltd.
Distributed by: Office of Postal Distribution of Henan Proince
Distributed Abroad by: Publishing Trading Corporation,P.O.B.782, Beijing100011, China
Publication Scope: Public Publication
Periodicity:Bimonthly
Founded in:1980
Code of Domestic Distribution: 36-232
Code of Overseas Distribution: BM2642
ISSN:1671-6833
CN:41-1339/T
CODEN:ZDXGAN

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