水利水电科技进展2011，Vol.31Issue(3)：13-16,4.DOI:10.3880/j.issn.1006-7647.2011.03.004
粒子群优化算法在确定越流含水层参数中的应用
Application of particle swarm optimization algorithm to determination of leakage aquifer parameters
摘要
Abstract
Based on the analytical solutions to well flow problems of unsteady flows in the first type leakage aquifer, the particle swarm optimization algorithm (PSO) was employed to analyze the data of pumping tests to determine aquifer parameters. Numerical experiments were conducted to study the influences of control parameters as acceleration constants c1 and c2 and inertia weight ω on the search capability of the PSO. The results show that the PSO can be effectively employed to analyze the data of pumping tests to determine the aquifer parameters for the first type leakage aquifer, and the precision of the outcomes is more objective. c1, c2 and ω have synthetic influences on the search ability in operation. When c1 = c2 = 2.0 and ω decreases linearly from 0.9 to 0.4 with the number of iterations, the particles can search among the global best location and their previous best locations with balanced probability, and the search capability can be kept properly.关键词
粒子群优化算法/含水层参数/越流系统/学习因子/惯性权重系数Key words
particle swarm optimization algorithm/ aquifer parameter/ leakage system/ acceleration constant/ inertia weight分类
建筑与水利引用本文复制引用
张鹄志,郭建青..粒子群优化算法在确定越流含水层参数中的应用[J].水利水电科技进展,2011,31(3):13-16,4.基金项目
国家重点基础研究发展计划(973计划)(2009CB421301) （973计划）
