Research on Water Resources Saving Based on Chaotic Particle Swarm Optimization

Authors

  • Yongcong Jiang Henan Forestry Vocational College, China

DOI:

https://doi.org/10.13052/spee1048-5236.4121

Keywords:

Water resources saving, chaotic particle swarm algorithm, optimal allocation of water resources.

Abstract

To improve the saving level of water resources, and the optimal allocation model of water resources is constructed, and the chaotic particle swarm optimization is established to solve the optimal allocation model. Firstly, the relevant researches are summarized, and the main contributions of this research are given. Secondly, optimal allocation conception of water resources is discussed, and then the corresponding optimal allocation model is established. Thirdly, the chaotic particle swarm optimization model is established, and the analysis procedure of the proposed algorithm is designed. Finally, optimal allocation analysis of water resources is carried out, and optimal allocation plans of water resources are confirmed, results show that the proposed optimal model and its solving algorithm can effectively obtain the best effect.

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Author Biography

Yongcong Jiang , Henan Forestry Vocational College, China

Jiang Yongcong, lecturer of Henan Forestry Vocational College, received his master’s degree of Computer Technology from Henan University of Science and Technology. He was awarded the title of Young Backbone Teacher of Henan Higher Vocational Colleges, Excellent Tutor of Henan Province and host of Excellent Online Open Course “Network Security” in Henan Province. He has won the second prize of Informatization Teaching Competition in National Vocational Colleges, the Gold Medal of the First National Forestry Innovation and Entrepreneurship Competition and the first prize of Teaching Achievement Award of China Communication Industry Association.

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Published

2022-04-04

How to Cite

Jiang , Y. . (2022). Research on Water Resources Saving Based on Chaotic Particle Swarm Optimization. Strategic Planning for Energy and the Environment, 41(2), 131–146. https://doi.org/10.13052/spee1048-5236.4121

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Articles