The Mixed Strategy Particle Swarm Optimization Algorithm for Determining Aquifer Parameters

China Rural Water and Hydropower ›› 2018 ›› (10) : 60-63.

DUAN Guo-rong，LIU Yuan-hui

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Abstract

Based on the conditions of infinitely aquifer and linear impervious boundary aquifer, the mixed strategy particle swarm optimization algorithm was applied to analyze the data of pumping tests for estimating aquifer parameters and provided a new method for estimating aquifer parameters. This mixed algorithm incorporates compaction into particle swarm optimizers algorithm to strengthen the local search ability of the algorithm. Combining with the control of scheduling coefficient to improve the convergence accuracy and speed. And the constraints of certain small probability improves global search ability. Then, the mixed strategy particle swarm optimization algorithm is established. The mixed algorithm can effectively solve the problem of slower convergence speed, poor accuracy and easily trapped into local extreme value, which appeared in particle swarm optimization algorithm. The results show that it is feasible method for estimating aquifer parameters. And the method has the advantage of high optimization accuracy, better convergence and better stability.

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aquifer parameters / particle swarm algorithm / compaction / scheduling

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DUAN Guo-rong, LIU Yuan-hui. The Mixed Strategy Particle Swarm Optimization Algorithm for Determining Aquifer Parameters . China Rural Water and Hydropower. 2018, 0(10): 60-63

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Natural Science Foundation of China

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Received	Revised	Published
2018-02-05	2018-05-09	2018-10-15
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2019-12-10

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