Water resource demand forecasting based on particle swarm optimization

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Water resource demand forecasting based on particle swarm optimization

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[1]Long Zhiwei,Xiao Songyi,Wang Hui,et al.Water resource demand forecasting based on particle swarm optimization[J].Journal of Zhengzhou University (Engineering Science),2019,40(04):32-35.[doi:10.13705/j.issn.1671-6833.2019.04.005]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 40 Number of periods: 2019 04 Page number: 32-35 Column: Public date: 2019-07-10

Title:: Water resource demand forecasting based on particle swarm optimization

Author(s):: Long Zhiwei 1; Xiao Songyi 2; Wang Hui 2; Zhou Xinyu 3; Li Wei 4; 1. Yaohu College, Nanchang Institute of Technology; 2. Jiangxi Provincial Key Laboratory of Water Information Collaborative Perception and Intelligent Processing, Nanchang Institute of Technology; 3. School of Computer Information Engineering, Jiangxi Normal University; 4. School of Information Engineering, Jiangxi University of Science and Technology

Keywords:: swarm intelligence; Particle swarm algorithm; water needs; predict; optimization

CLC:: TP18

DOI:: 10.13705/j.issn.1671-6833.2019.04.005

Abstract:: Aiming at the problem of predicting the future demand of water resources in Nanchang, a water resource demand forecasting method based on particle swarm optimization algorithm is proposed. Based on the historical population, economy and water demand data of Nanchang City, linear, exponential and mixed forecasting models are constructed. The algorithm optimizes the prediction model to determine the model parameters. The simulation experiment results show that all three models can obtain good prediction accuracy, and the hybrid prediction model is the best, with a prediction accuracy of 97.71%.

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Last Update: 2019-07-29