2024 volumne 45 Issue 04
YANG Shouyi1, CHEN Yihang1, ZHANG Shuangling2, HAN Haojin1, LI Guangyuan3, HAO Wanming1
Abstract: Mobile edge computing (MEC) has become one of the key technologies for future-oriented communica tions by offloading the computing and storage tasks of mobile terminals from centralized data centers to edge grids to satisfy the diverse device service demands in complex communication scenarios. The basic concept and basic frame work of MEC technology were introduced by describing the development history from cloud computing, fog compu ting to mobile edge computing. On this basis, the research progress of MEC was discussed in four aspects, namely, computation offloading, resource allocation, cache management, and security protection. A detailed overview of the relevant research results was provided. Then, studies on several typical application scenarios of edge computing such as IoT, MEC combined with blockchain, AI-assisted MEC systems, integrated sensing and communication, and cloud-edge collaboration were summarized. It demonstrated the potential benefits of MEC in 6G in terms of con stituting an intelligent, efficient and secure communication network. Finally, the challenges faced by MEC research in convergence innovation from the aspects of interoperability, security risk, mobility management and scalability were pointed out, as well as the advantages and development trends in the directions of ultra-reliable low-latency communications, communication-sensing-computing integration and satellite-ground fusion mobile communication. The development trend of it in the future mobile communication was also summarized and outlooked.
SHE Wei1,2,3, KONG Xiangji1,3, GUO Shuming2,4, TIAN Zhao1,3, LI Yinghao1,2,3
Abstract: Based on deep learning MVS methods, neural networks suffered from a large number of parameters and high GPU memory consumption. To address this issue, a lightweight deep convolutional recurrent network recurrent network-based MVS method was proposed. Firstly, the original images passed through a lightweight multi-scale fea ture extraction network to obtain high-level semantic feature maps. Then, a sparse cost volume to reduce the com putational workload was constructed. Next, GPU memory consumption was reduced by using a simple plane sweep ing technique that utilized by a convolutional recurrent network for cost volume regularization. Finally, sparse depth maps were extended to dense depth maps using an extension module. With a refinement algorithm, the proposed approach achieved a certain level of accuracy. The proposed approach was compared to state-of-the-art methods on the DTU dataset including traditonal MVS methods Camp, Furu, Tola, and Gipuma, and also including deep learn ing-based MVS methods SurfaceNet, PU-Net, MVSNet, R-MVSNet, Point-MVSNet, Fast-MVSNet, GBI-Net, and TransMVSNet. The results demonstrated that the proposed approach reduced GPU consumption to approximately 3.1 GB during the prediction stage, and the differences in precision compared to other methods were relatively small.
ZHI Min, LU Jingfang
Abstract: ViT as a model based on the Transformer architecture has shown good results in image classification tasks. In this study, the application of ViT on image classification tasks was systematically summarized. Firstly, the functional characteristics of the ViT framework and its four modules (patch module, position encoding, multihead attention mechanism and feed-forward neural network) were briefly introduced. Secondly, the application of ViT in image classification tasks was summarized with the improvement measures of the four modules. Due to the fact that different model structures and improvement measures could have a significant impact on the final classification performance, a side-by-side comparison of various types of ViTs was made in this paper. Finally, the advantages and limitations of ViT in image classification were pointed out, and possible future research directions were proposed to break the limitations, and further to extend the application of ViT in other computer vision tasks. The extension of ViT to a wider range of computer vision fields, such as video understanding, was explored.
WEI Mingjun1,2, LI Feng1, LIU Yazhi1,2, LI Hui1
Abstract: In order to protect the Internet of Vehicles system from the threat of network attacks and improve the ac curacy of intrusion detection, a new intrusion detection method (AQVAE-RGSNet) was proposed for the character istics of large data flow and unbalanced attack types in the vehicle network. Firstly, the adversarial quantized varia tional auto encoder was used to process the vehicle network data imbalance. And it was constructed by combining the vector quantized variational auto encoder-2 and the generative adversarial network with gradient penalty to alle viate the extremely unbalanced number of samples of abnormal attack types in the dataset. Afterwards, the ResNet and improved segmented residual neural network were used to learn the input sample data and predict its attack cat egory. The experimental results indicated that AQVAE-RGSNet achieved F1 scores of 0.998 6 and 0.999 7 on the vehicle networking dataset CICDS2017 and CAN-intrusion-dataset, respectively. On the premise of ensuring the best training effect, it could identify attack threats more effectively in the vehicle network.
SUN Xiaochuan1,2, WANG Yu1,2, LI Yingqi1,2, HUANG Tianyu1,2
Abstract: To address the problem of undesirable prediction accuracy of a deep echo state network caused by redun dant structures in the reservoirs, a pruning algorithm for the deep echo state network based on detrended multiple cross-correlation was proposed. Firstly, according to the detrended covariance function and the detrended variance function, the detrended cross-correlation coefficient between each two neurons in the selected reservoirs in turn was calculated, and the detrended cross-correlation matrix was constructed. Based on this matrix, the detrended multi ple cross-correlation between a selected neuron and all remaining neurons in this reservoir could be evaluated. Sub sequently, the connections from the highly correlated neurons in each reservoir to the output layer were pruned se quentially, thus removing redundant components in the network. Finally, the network after pruning was retrained by least squares regression to obtain the optimal deep echo state network topology. Simulation results showed that the prediction accuracy and memory capacity of the deep echo state network optimized by the proposed algorithm on Mackey-Glass time series were improved by 89.80% and 30.93%, respectively, and on Call time series by 14.34% and 0.10%, respectively.
LI Zhixin1, SHANG Fanqi1, HUAN Zhan1, CHEN Ying1, LIANG Jiuzhen2
Abstract: The existing methods for human activity recognition using wearable sensors could not capture the struc tural information between the sampling points of time series effectively and might ignore the potential connections between samples. To address this issue, a graph convolutional neural network model with hybrid time-frequency and structural characteristics was proposed for human activity recognition. Firstly, the time-frequency characteris tics of the original signal were obtained by wavelet-packet transform, and the spatio-temporal graph was further con structed to extract the structural characteristics to identify the dynamic characteristics between the sampling points. The distance constraint was added to the structural characteristics to weaken the influence of long-distance neighbors on the central node on the spatio-temporal graph. Considering that the extraction of structural characteristics was greatly affected by the topological relationship of the spatio-temporal graph. The time-frequency characteristics of the samples to construct the input topology of the graph convolutional neural network were selected, and the time frequency and structural characteristics were combined as the input features of the network. Finally, the input fea tures propagated along the input topology to obtain the final classification result. To evaluate the performance of the proposed model, experiments were conducted on the WHARF and DataEgo datasets. Results in terms of F1 scores indicated that the proposed model outperformed existing convolutional neural network-based methods, achieving a maximum improvement of 19.58 percentage points on the WHARF dataset and 26.44 percentage points on the Da taEgo dataset. It demonstrated that the proposed model could effectively enhance the capability of activity recogni tion by exploiting dynamic characteristics.
LI Weijun, GU Jianlai, ZHANG Xinyong, GAO Yuxiao, LIU Jintong
Abstract: In few-show knowledge graphs, the representation of relationships between entity pairs was diverse and complex. However, existing few-show knowledge graph completion methods commonly suffered from insufficient re lational learning capabilities and the neglect of contextual semantics associated with entities. To address these chal lenges, a novel approach called the few-shot relation learning completion model (FRLC) was proposed. Firstly, during the process of aggregating high-order neighborhood entity information, a gating mechanism was introduced to mitigate the adverse effects of noise on neighbors while enriching the representation of central entities. Secondly, in the phase of relation representation learning, the correlations among entity pairs in a reference set were leveraged to obtain more accurate relationship representations. Lastly, within the Transformer-based learning framework, an LSTM structure was incorporated to further capture contextual semantic information of entities and relationships, which was used for predicting new factual knowledge. To validate the effectiveness of FRLC, comparative experi ments were conducted on the publicly available NELL-One and Wiki-One datasets, in which FRLC was compared with six few-shot knowledge graph completion models and five traditional models for 5-shot link prediction. The ex perimental results showed improvements in FRLC across four metrics: MRR, Hits@10, Hits@5, and Hits@1, demonstrating the model′s effectiveness.
SUN Jian1,2, LIU Pin1, LI Hao1, CHEN Pan1
Abstract: A two-stage KSAGA algorithm combining Spark-based simulated annealing and genetic algorithms was proposed for the single-depot multiple traveling salesman problem with minimum total path length. In the first stage, the multiple traveling salesman problem was split into multiple single traveling salesman problems by k means clustering, and the traversal order of cities in the group was optimized using the simulated annealing algo rithm. In the second stage, the classification of cities was optimized by genetic algorithm, and the cross-variance operator as well as the hybrid local optimization operator were designed based on the chromosome grouping encoding method to improve the search space and convergence speed of the algorithm. As the number of cities increased and the computational scale became larger, the characteristics of genetic algorithm were used to realize the parallelism of the algorithm in order to speed up the algorithm operation efficiency. Finally, the solution quality of KSAGA was compared with that of ACO, GA, SPKSA, ALNS and NSGA-Ⅱ and the convergence speed of GA and NSGA-Ⅱ by selecting some datasets of TSPLIB for simulation experiments. The results showed that KSAGA could converge quickly in solving the single-depot multiple traveling salesman problem, and the solution quality was greatly im proved compared with other algorithms. Meanwhile, the advantage of KSAGA was more obvious as the number of cities and the number of travelers increased.
GUAN Changshan, BING Wanlong, LIU Yahui, GU Pengfei, MA Hongliang
Abstract: At present, most rumor detection work mainly based on the original text content, communication struc ture and communication text content of Twitter or Weibo. However, these methods ignored the effective integration of original text features with other features, as well as the role of propagating users in the process of rumor propaga tion. Aiming at the shortcomings of the existing work, a multi-feature fusion model GCNs-BERT based on graph convolutional network was proposed, which combined the features of the original text, the propagating user and the propagating structure. Firstly, a propagation graph was constructed based on the propagation structure and the prop agation users, and the combination of multiple user attributes was used as the propagation node feature. Then, mul tiple graph convolutional networks were used to learn the representation of the propagation graph with different user attribute combinations, and BERT model was used to learn the feature representation of the original text content. Finally, the fusion with the features learned by the graph convolutional network was used to detect rumors. A large number of experiments using publicly available Weibo data sets showed that the GCNs-BERT model was significant ly better than the baseline method. In addition, the generalization ability experiment of GCNs-BERT model was conducted on the novel coronavirus epidemic data set. The training sample size of this data set was only 1/5 of that of the public Weibo data set, and the accuracy rate was still 92.5%, which proved that the model had good gener alization ability.
MAO Wentao1,2, GAO Xiang1, LUO Tiejun3, ZHANG Yanna1,2, SONG Zhaoyu1
Abstract: In the actual business, parts demand occured randomly and demand fluctuates, so the demand sequence for spare parts showed obvious intermittent distribution. At the same time, due to factors such as manual reporting errors or special events, the actual demand for spare parts was prone to abnormal changes, making it difficult for traditional time series prediction methods to capture the evolution of the demand for accessories, resulting in high uncertainty and insufficient reliability of prediction results. To solve this problem, an adaptive interval prediction method for intermittent series based on tensor representation was proposed. Firstly, hierarchical clustering was used to screen similar sequences based on the average demand interval and square of the coefficient of variation of acces sory sequences, forming sequence clusters to increase predictability. Secondly, the original demand sequence was reconstructed by tensor decomposition. The outliers in the sequence were then corrected while retaining the core in formation of the original sequence to maximum extent. Finally, an adaptive prediction interval algorithm was con structed, which could obtain the predicted value and prediction interval of the parts demand through the dynamic update mechanism to ensure the reliability of the results. The proposed method was validated on the aftersales data set from a large vehicle manufacturing enterprise. Compared with existing time series prediction methods, the pro posed method could effectively extract the evolutionary trend of various types of intermittent series and improve the prediction accuracy on the intermittent time series with small size as well. Experiments showed that the average root mean square scaled error (RMSSE) of this method was 0.32 lower than that of the mainstream in-depth learning method of demand prediction. More importantly, when the prediction results were distorted, the proposed method could provide a reliable and flexible prediction interval, which could be helpful to provide a feasible solution for in telligent parts management.
DOU Ming1, YAN Jiajia1, WANG Cai2, GUAN Jian3, LI Guiqiu1, HOU Jinjin4
Abstract: In view of the lack of studies on the impact of low impact development (LID) spatial layout on the con trol effect of water quantity and quality, Zhongyuan District of Zhengzhou City as a target area, its urban water quantity and quality model with LID facilities was built based on SWMM model principle. Based on the empirical value of urban comprehensive runoff coefficient and the actual situation of the area, Zhongyuan District was divided into high, medium and low-density areas of urban buildings, and different proportions of LID (S1-S5) were de ployed in the high, medium and low-density urban areas, and the control effect of different spatial patterns of LID facilities on water quantity and quality under different rainfall levels was calculated. The results showed that with the increase of rainfall level, the total runoff reduction rate, peak flow reduction rate and TSS load reduction rate of LID scheme continued to decrease. When rainfall levels were rainstorm, heavy rain and moderate rain, LID scheme (S5) with a proportion of 35%, 35% and 30% were deployed in high, medium and low dense urban areas, and the total runoff reduction rate exceeded 80%, the peak flow reduction rate exceeded 70%, and the TSS load reduc tion rate exceeded 50%. From the comprehensive index evaluation of water quantity and water quality in each e vent, the program had the best performance.
HUANG Li1,2, WANG Yunqing3, WANG Wei2,3, SONG Yue2,3, SHI Yuxin3
Abstract: In order to prevent and reduce the disaster losses caused by compound disasters to cities, it was of great theoretical and practical significance to study the exposure degree of chain compound disaster system. Through the research and analysis of the exposure degree of chain compound disaster system, considering the existing research and defining the connotation of the exposure degree of the compound disaster system, the evaluation model and cal culation method of the exposure degree of the chain compound disaster system were deduced and established. Tak ing the rainstorm-landslide disaster chain in Guangdong-Hong Kong-Macao Greater Bay Area as an example for em pirical analysis, the evaluation index system of regional disaster chain exposure was screened and constructed from the aspects of population, economy and society. The order relationship analysis and TOPSIS method were used to calculate the single disaster exposure index of rainstorm and landslide in 52 districts and counties in the bay area. Then, the theoretical model of exposure degree of chain compound disaster system and ArcGIS image processing technology were used to obtain the zoning map of rainstorm-landslide disaster chain exposure in the Guangdong Hong Kong-Macao Greater Bay Area, and the corresponding disaster prevention and mitigation measures were put forward according to the exposure degree attribute of each regional disaster chain. The results showed that the expo sure index corresponding to the economically developed areas was significantly higher than that of other regions, and the low exposure were mainly in the relatively backward areas. Among the indicators, population density and GDP per land area account for the main position, which had the highest impact on regional exposure. By the exposure of regional compound disaster systems, reasonable scientific basis and decision-making support could serve for the government and relevant departments, helping the government, urban planners, and the public better understand and respond to disaster risks, thereby reduce the losses and impacts of disasters.
WAN Junfeng1, 2, SONG Yifan1, 2, GUO Lin3, MA Yifei1,2, LI Zhe1, 2, DING Junxiang1, GUO Xiaoying1, 2
Abstract: In order to analyze the different types of influence of human disturbance on plant communities in the Yellow River wetland and the relevant mechanisms, three wetlands in Zhengzhou section which were respectively affected by agricultural planting, reservoir construction and building construction, were selected after conducting a large number of field investigations. After measuring the plant communities and related environmental factors, redundancy analysis was carried out based on human pressure index evaluation system. The results showed that the whole wetland plant community showed an obvious degradation trend, and the function of productivity maintenance decreased. For the sample land with different types of human disturbance, the severity of human disturbance varied from the disturbance caused by reservoir construction to agricultural planting, and building construction. With intensification of the severity of human disturbance, the similarity coefficients of plant communities in different wet lands declined successively, and the species richness index of wetland in Bird Nature Reserve and Taipingzhuang North wetland decreased by 15.98% and 37.05%, respectively, compared with the Taohuayu wetland, indicating that the overall construction of wetland plant communities gradually became simpler. Among the many factors causing wetland degradation, the change of ammonium nitrogen content in soil had a significant negative correlation with species diversity index and species evenness index, and was one of the main reasons for wetland plant degradation.
KUANG Yida1, YAO Zhimin2, BIAN Huiting1, ZHAO Jun1, LI Xinzhe1, ZHANG Lijuan1
Abstract: To study the influences of fire extinguishing agents on the mechanical performance of concretes after high temperatures, specimens of different curing ages were heated to different temperatures at 5 ℃/min and 10 ℃/min heating rates, and then they were maintained at different constant temperatures of 200 ℃, 400 ℃, 600 ℃ and 800 ℃ for one hour. The mass loss rate of specimens of different curing ages and heating temperatures were tested. Specimens were moved into a tempered glass frame. Water, Halon 1211, CO2 and HFC-227ea were used to treat these specimens. The results showed that the mass loss rates of the specimen with 7 d and 14 d curing age were sig nificantly higher than that in 28 d curing age at 400 ℃. Fire extinguishing agents did not affect the compressive strength of the specimens at room temperature. Water, Halon 1211, and HFC-227ea could reduce compressive strength of the specimens after high temperature treatment at 400 ℃ and 600 ℃. However, water cooling treatment at 600 ℃ could increase the compressive strength of the specimen with 7 d and 14 d curing age by 9.14% and 9.18%. Curing age did not affect the experimental results of Halon 1211 and HFC-227ea, and the compressive strength of the specimen was relatively low at 800 ℃, which could not reflect the influence of different treatment methods on the compressive strength. Water, Halon 1211, and HFC-227ea fire extinguishing agents could reduce the splitting tensile strength of concrete at 400 ℃. CO2 had no influence on the compressive strength and splitting tensile strength of concrete.
LIAO Xiaohui1, XIE Zichen1, XIN Zhongliang2, CHEN Yi1, YE Liangjin1
Abstract: In order to improve the accuracy of real-time detection of external defects of electrical equipment in sub stations and make the detection model more lightweight, a lightweight YOLOv5 based external defect detection method for electrical equipment was proposed. Firstly, the external defect image dataset of electrical equipment was constructed and processed by data enhancement. Secondly, three optimization strategies were used to improve the original YOLOv5. The EfficientViT network was introduced to improve the backbone network of the algorithm to re duce the number of model parameters, and the SimAM parameter-free attention mechanism was added to the Neck part of the algorithm to improve the recognition accuracy with the complex background of the substation. At the same time, the Soft-NMS module was used to improve the screening method of the detection box to avoid the phe nomenon of defect missed detection. Finally, verified by ablation test, the mAP value of the lightweight external de fect detection model of electrical equipment was stable at 86.4%, which was 1.2 percentage points higher than that of the original model, the number of model parameters were reduced by 20%, the calculation amount was reduced by 38%, and the model size was 11 MB, which was 19.7% lower than that of the original model. The improved model could meet the requirements of real-time detection of external defects of equipment.
JIANG Xin, DUAN Shijie, JIN Yang, SHANG Jingyi
Abstract: Due to the difference of the physical constraints of traded goods and trading time scale in the electricity market and the carbon market are different, it was difficult for the two markets to integrate effectively. Aiming at the problem, a rolling clearing model of the electro-carbon joint market based on the variable carbon emission inten sity and the centralized carbon trading mechanism was proposed. In the proposed model, the interaction between the electricity market and the carbon market was enhanced by considering the carbon intensity and load rate interval of the unit. Meanwhile, the rolling clearance of the joint market based on the centralized carbon trading mechanism reduced the trading time scale of the carbon market to synchronize with the electricity market, making it′s better to found the value of carbon emission rights in different periods. With the further reduction of China′s carbon emission baseline value and the increase of new energy penetration rate, the impact on each unit was analyzed by simulation examples. It was verified that in the proposed model, with the reduction of the carbon emission baseline value, the average carbon cost of high-carbon emission units increased by 46%, the average carbon income of low-carbon e mission units increased by 27%, and the increase in the penetration rate of new energy units reduced the average carbon cost of the large-capacity thermal power units by 5.53%. Therefore, the proposed model could effectively promote the transformation of the clean direction of the system. Compared with the traditional stepped carbon pricing mechanism, the average carbon cost of high-carbon emission units in the proposed model was reduced by 6.13%, which could indirectly improve the enthusiasm of high-carbon emission units to participate in the carbon market.
LIANG Jie, SUN Zhenwei
Abstract: Aiming at the problems of low efficiency and inability in accurate assessment of the roundness and flatness of air conditioning compressor crankshaft, which were measured manually with a micrometer, a set of non-con tact measurement system of roundness and flatness of air conditioning compressor crankshaft based on a line laser displacement sensor was designed. Firstly, a calibration method of systematic error was proposed by measuring a standard measuring rod. Then, based on the line laser sampling data, an extraction algorithm of crankshaft cross section roundness measurement points was developed, and the systematic error was used for the compensation of the measurement points to realize the roundness measurement of the crankshaft. After that, the contour line was separa ted according to the slope between the measurement points of the crankshaft plane, and the streamlined point cloud data were obtained by the homogeneous down sampling method, and the least square method was used to realize the flatness measurement of the crankshaft. Finally, the crankshaft roundness and flatness measurement experiments were carried out based on the above methods. The experimental results showed that the roundness measurement ac curacy of the system was less than 4 μm, the flatness measurement accuracy was less than 2 μm, the repeatability error of roundness measurement was less than 0.8 μm, and the repeatability error of flatness measurement was less than 0.3 μm, which could satisfy the requirements of fast and accurate measurement of roundness and flatness of crankshaft.
ZHOU Juncen, GAN Fangji, WANG Siyu, ZHONG Tao, YANG Suixian
Abstract: Ultrasonic guided wave technology was often used for wall thickness monitoring system of high tempera ture pipelines because it could isolate the ultrasonic transducer from the high temperature environment. However, the failure of conventional coupling technology and the low signal-to-noise ratio of the signal at high temperature af fected the reliability and measurement accuracy of the measurement system. A waveguide rod was designed to con duct ultrasonic signals. Based on the acoustic matching principle, the dry coupling technology was optimized to solve the failure problem of conventional coupling technology in high temperature environment. The adaptive excita tion method and the power multiplication algorithm of measurement data were proposed to improve the adaptability and signal-to-noise ratio of the measurement system at high temperature. Intelligent segmentation of the speed of sound was used to correct the speed of sound, and the method made the measurement accuracy of the high-tempera ture ultrasonic guided wave thickness measurement system reach ±0.03 mm. The experimental results showed that the temperature of the ultrasonic transducer end was not more than 56 ℃ at the maximum under the environment of a long term heat source of 500 ℃, which verified the reliability of the measurement system in high temperature en vironments.
Pre-publication   
LI Ruixia,LI Jiahui,JIANG Zhifu,ZHANG Yadong,YUE Jinzhao
Abstract: In order to reduce the content of carcinogenic polycyclic aromatic hydrocarbons in coal asphalt and realize its green application, polyurethane monomer, trioxymethylene, polyethylene glycol, divinyl benzene and epoxy resin were respectively used to react with coal-tar pitch alone or mixed. The removal rate of benzo [ a ] pyrene( BaP) , a representative carcinogen in coal-tar pitch, was used as an evaluation index to analyze the effects of each single modifier and composite modifier on BaP in coal-tar pitch. The results showed that all the selected modifiers can effectively reduce the content of BaP in coal-tar pitch, the order of detoxification effect of a single modifier in descending is polyurethane monomer>trioxymethylene>polyethylene glycol>divinyl benzene>epoxy resin; the optimal combination of composite modifiers is 6% polyurethane monomer+ 10% trioxymethylene+ 8% polyethylene glycol, which removal rate of BaP can reach 82. 16% under the optimal reaction conditions.
QIN Dongchen, ZHAO Hongfei, WU Hongxia, YANG Junjie, CHEN Jiangyi, WANG Tingting
Abstract: In order to solve the problem of inconsistent capacity of single battery in battery pack, the active equalization control technology of battery pack in series was studied, including the improvement of equalization topology and the design of equalization control strategy. Firstly, a new balanced topology is proposed and verified. Secondly, the mathematical model of the equalization circuit is established, and the effects of voltage difference and switching frequency on the equalization performance are analyzed. According to the results of voltage difference analysis, a many-to-many equalization control strategy based on variable duty cycle is designed to improve the equalization speed and equalization consistency. Finally, in MATLAB\ / Simulink, the equilibrium topology and the algorithm of co-simulation. The results show that compared with the fixed packet equalization control strategy, the proposed equalization topology and control strategy can improve the equalization speed and equalization consistency of the battery pack. The equalization time is reduced by 29.71%, the SOC variance of the charged state of the battery is reduced by 16.13%, and the number of energy transfers during the equalization process is reduced by 52.5%.
QIN Dongchen, ZHANG Wencan, WANG Tingting, CHEN Jiangyi
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.
ZHAO Dong, LI Yarui, WANG Wenxiang, SONG Wei
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.
ZHANG Junfeng, HU Lianchao, WU Jingjiang, GENG Yupeng, LI Jie
Abstract: The study was initiated for the consistent mass matrix of Euler beam element including shear deformation. The consistent mass matrix of uniform element was got separately for the uncoupled tension, torsion, and bending conditions, with the shear deformation included or not, based on the shape functions and the virtual work. It was shown that the inertia force along the axial direction is always ignored in the mass matrix derivation for the bending condition if the shear deformation in not included, so only the shape functions for vertical deformation are needed for the bending condition. When the shear deformation is included, the inertia force along the axial direction must be considered and the shape functions for the section rotation angle due to bending are also required besides the complete shape functions for vertical deformation due to the bending and shear forces. For tapered Euler element, the theoretical expression for the consistent mass matrix would be quite complicated and a simple expression was proposed following an approximate strategy: matching the ending or average section areas or polar moments with the elements in the mass matrix according to their positions. Additionally, the stiffness matrix could also be deduced on the foundation of the complete shape functions for vertical deformation and the shape functions for the section rotation angle. This derivation procedure is different with the traditional manner superficially but they share thesame principle essentially.
Bi Ying,Xue Bing,Zhang Mengjie
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.
Wang Wen1,Hu Haoliang1,He Shitang1,Pan Yong2,Zhang Caihong3
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.
Li Yanyan 1,Yang Haotian 2,Zeng Yufan 3
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
Huang Yuda; Wang Yanran; Niu Sijie;
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.
Wang Jianming; Qiu Qinyu; He Xunchao
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.
Zhao Shufang, Dong Xiaoyu
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. 
Jiang Yang1,Guo Jiankun 1,Wang Xiaomou 2,Hou Chaoqun 3
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

Han Chuang, Wu Lili
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.
Zhou Junjie, Wang Pu, Zhou Jinfang
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.
CHEN Deliang,DONG Huina,ZHANG Rui
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.
Zhang Heng, Wang Heshan
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.
Shi Chunyan1,Fan Bingbing1,Li Yaya1,Hu Yongbao1,Zhang Rui2
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.
Li Yifeng, Mao Xiaobo, Yang Yihang, Zhu Feng
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.
JIAO Liu-cheng,YAO Tao
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.
Maling1,Jiang Huiqin1,Liu Yumin2
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.
Li Cailin, Chen Wenhe, Wang Jiangmei, Tian Pengyan, Yao Jili
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.
Sun Xiaoyan, Zhu Lixia, Chen Yang
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.
Liang Jing1,Liu Rui1,Qu Boyang2,Yue Caitong1
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.
Mao Xiaobo, Zhang Qun,Liang Jing, Liu Yanhong
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.
Liu Qian; Feng Yanhong; Chen Yingying;
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.
WAN Ya-zhen,LIU Ya-nan,CHEN Di
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.
Zhao Huadong, Jiangnan, Lei Chaofan
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.
LIU Zhenghua1, WANG Jing2,DU Haiying’1,2
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.
Liu Guangrui; Zhou Wenbo; Tian Xin; Guo Kefu
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.
Li Haibin1,Ke Shengwang2,Shen Yanjun2
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.
Mao Xiaobo, Hao Xiangdong, Liang Jing
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.
Dong Chee-hwa1,Wang Guoyin2,Yongxi3,Shi Xiaoyu2,Li Qingliang4
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.
Liu Yanhong, Zhao Jinglong
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
Wei Ran
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.
Sheng Zunrong1,Xue Bing1,Liu Zhouming1,Wei Xinli2
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.
Cao Ben, Yuan Zhong, Yu Liu Hong
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.
Deng Jicai, Geng Yanan
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.
Ding Guoqiang1Zhang Duo1Xiong Ming1Zhou Weidong2
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.
Xiao Junming, Zhou Qian, Qu Boyang, Wei Xuehui
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.
ZHU Yazhong,LI Shunyi,LUO Yimeng ,MA Hongye,WANG Yan
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.
LIU Zhi-fang,LIU Xin-hong,HUANG Ya-lei,MA Teng
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.
JIANG Jian-dong1 ,ZHANG Hao-jie1 ,WANG Jing2
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.
Hu Xiaobing, Xie Zhenfang, Xie Ji, Xie Lili, Zhu Zhigang
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.
Ding Chang, Fu Yantang, Wu Xuehong, Gong Yi
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.
LIU Min-shan,XU Wei-feng ,JIN Zun-long,WANG Yong-qing,WANG Dan
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 % .
FANGShuqi1,2,HELiping1,ZHANGLonglong1,CHANGChun1,2,BAI Jing1,2,CHENJunying1,
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.
FENG Dong-qing,XING Kai-li
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.
Deng Shaohong 1,Li Ling 1Guibin 2
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
Li Jingli, He Pengwei, Qiu Zaisen, Li Yuanbo, Guo Liying
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.
Chen Tiejun, Cai Jinshou, Guo Li
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.
Zhang Zhonghui, Liu Gushuai, Xiong Jianfeng, Liu Xiaowan, Xu Gaochao
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.
Dai Pinqiang1,Song Lairui2,Cui Zhixiang3,Wang Qianting3
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.
Wang Dongshu, Tan Dapei, Wei Xiaoqin
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%.
MU Xiaomin , SHI Guangqiang,LIU Ying , YANG Shouyi
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.
CHEN Deliang,DONG Huina,ZHANG Rui
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.
RONG Xian,SONG Peng,ZHANG Jianxin,etc;
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.
Zhao Shujun, Duan Shaoli, Zhang Xiaofang, Li Lei, Liu Xiaomin
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.
Li Yifeng, Mao Xiaobo, Yang Yihang, Zhu Feng
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.
Li Lingjun, Jin Bingma, Yanli Han, Jie Hao, Wang body
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.
Han Chuang, Wu Lili
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.
Li Guang1, Zhang Heng2, Wang Jie2, Zhu Xiaodong2, Yue Caitong2
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.
ZHANG Chunjiang1,2,TAN Kay Chen2,GAO Liang1, wU qing3
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.
Liu Ke 1;Gong Dunwei 2
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.
Shen Chao1,Yu Peng1,Yang Jianzhong1,Zhang Dongwei2,Wei Xinli2
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.   
Dong Chee-hwa1,Wang Guoyin2,Yongxi3,Shi Xiaoyu2,Li Qingliang4
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.
Zhao Fengxia , Jin Shaobo , Li Jifeng
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.
Cheng Shi 1,Wang Rui 2,Wu Guohua 3,Guo Yinan 4,Malembo 5,Shi Yuhui 6
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.
Cong PeiLIANG,LIU Jianfei,ZHAO Zhiqiang,etc;
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.
WANG Qinghai1,ZHAO Fengxia2,Ll Jifeng2,JIN Shaobo2
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.
Li Jingli, He Pengwei, Qiu Zaisen, Li Yuanbo, Guo Liying
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.
ZHU Xiaodong,LIU Chong,GUO Yamo
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.
Sun Xiaoyan, Zhu Lixia, Chen Yang
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.
ZHENG Yuanxun ,YANG Peibing
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.
FANGShuqi1,2,HELiping1,ZHANGLonglong1,CHANGChun1,2,BAI Jing1,2,CHENJunying1,
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.
Liang Jing1,Liu Rui1,Qu Boyang2,Yue Caitong1
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.
JIANG Jian-dong1 ,ZHANG Hao-jie1 ,WANG Jing2
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.
WANG Peng , FAN Lei,CUI Can
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.
Shi Chunyan1,Fan Bingbing1,Li Yaya1,Hu Yongbao1,Zhang Rui2
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.
Liu Guangrui; Zhou Wenbo; Tian Xin; Guo Kefu
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.
Zhang Heng, Wang Heshan
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.
Mao Xiaobo, Zhang Qun,Liang Jing, Liu Yanhong
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.
Liu Yanping Wei Hanghang, Li Qian
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.
Wang Dongshu, Tan Dapei, Wei Xiaoqin
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%.
Dai Pinqiang1,Song Lairui2,Cui Zhixiang3,Wang Qianting3
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.
Wang Wen1,Hu Haoliang1,He Shitang1,Pan Yong2,Zhang Caihong3
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.
Sheng Zunrong1,Xue Bing1,Liu Zhouming1,Wei Xinli2
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.
ZHAO Guosheng1,NIU Zhenzhen1,LIU Yongguang2, SUN Chaoliang2
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.
Mao Xiaobo, Hao Xiangdong, Liang Jing
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.
Bi Ying,Xue Bing,Zhang Mengjie
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.
Zhang Yang; Si Guangya; Wang Yanzheng
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
JIAO Liu-cheng,YAO Tao
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.
Zhou Junjie, Wang Pu, Zhou Jinfang
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.
Maling1,Jiang Huiqin1,Liu Yumin2
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.
Cao Ben, Yuan Zhong, Yu Liu Hong
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.
WANG Wei-shu1, SHAGN GUAN Shan-shan1,LU Tong1 ,YANG Zhi-feng2 ,ZHENG Chun-xiong1,CHEN Gang1
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.
LIU Min-shan,XU Wei-feng ,JIN Zun-long,WANG Yong-qing,WANG Dan
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 % .
CHEN Xiaopan1 ,QU Jiantao1,2,ZHAO Yameng2, WANG Peng1, 2 , CHEN Yulin1
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.
Li Haibin1,Ke Shengwang2,Shen Yanjun2
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.
Hu Xiaobing, Xie Zhenfang, Xie Ji, Xie Lili, Zhu Zhigang
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.
Zhang Zhonghui, Liu Gushuai, Xiong Jianfeng, Liu Xiaowan, Xu Gaochao
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.
MU Xiaomin , SHI Guangqiang,LIU Ying , YANG Shouyi
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.
Jiang Yuewen, Qian Jiaqi
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
Ding Chang, Fu Yantang, Wu Xuehong, Gong Yi
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.
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
QR Code
Selected Covers
Copyright © 2023 Editorial Board of Journal of Zhengzhou University (Engineering Science)