Abstract
The purpose of this study was to investigate improve the utilization rate of water resources and using multi-objective optimization algorithms to prediction water demand for the next 30 years, then the swarm intelligence approach was used to analysis for the development and utilization of water resources. The results obtained in this study include built a group optimization intelligent algorithm and the multi-objective optimization configuration prediction model for water resources is realized, for the disadvantages of PSO and GA algorithm, a hybrid optimization algorithm based on PSO and GA is proposed. The results indicated that the proposed algorithm can predict the water demand in the next 30 years, and can provide a certain reference for the formulation to effective regulation economic, social and ecological water consumption. Simultaneously, the PSO and GA hybrid optimization algorithm can achieve more than a simple algorithm using PSO or GA optimization results better.
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Acknowledgements
This work is partially supported by the Natural Science and Technology Project Plan in Yulin of China (2019-78-2, 2019-78-1, 2019-76-2, 2019-106-6, 2016CXY-12-09), Funding Project for Department of Yulin University (16GK24,TZRC1801), and thanks for the help.
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Communicated by: H. Babaie
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Zhang, F., Zhang, Y. A multi-objective optimization prediction approach for water resources based on swarm intelligence. Earth Sci Inform 14, 457–468 (2021). https://doi.org/10.1007/s12145-020-00521-1
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DOI: https://doi.org/10.1007/s12145-020-00521-1