水资源与水工程学报2017，Vol.28Issue(1)：100-103,4.DOI:10.11705/j.issn.1672-643X.2017.01.17
改进粒子群算法在确定含水层参数中的应用
Applications of the improved particle swarm algorithm to estimate aquifer parameters
摘要
Abstract
To analyze pumping test data can supply a new method for estimating aquifer parameters.The particle swarm algorithm improved in terms of particle diversity increased convergence speed and accuracy of the algorithm.The improved particle swarm optimization algorithm was applied to estimate the aquifer parameters.The calculated results were compared with the other methods,and the estimated values of parameters under different initial scopes were analyzed and discussed.The results showed that,the relative errors of improved particle swarm algorithm (which were 7.3％ and 4.5％,respectively) were smaller than the relative errors of the other methods,and the objective function value was also relatively smaller,reaching 0.335 × 10-5;For different initial parameter ranges,the improved algorithm obatined a satisfactory parameter estimation result and maintained a high rate of optimization search.Based on pumping test data,the results of improved particle swarm optimization algorithm for estimating aquifer parameters were more effective and reliable with fast convergence speed,strong optimization ability and good stability.关键词
含水层参数/粒子群算法/参数估计/抽水试验Key words
aquifer parameter/particle swarm optimization/parameter estimation/pumping test分类
建筑与水利引用本文复制引用
杨陈东,常安定,李文胜,张明..改进粒子群算法在确定含水层参数中的应用[J].水资源与水工程学报,2017,28(1):100-103,4.基金项目
陕西省教育厅科研计划项目(16JK1394) （16JK1394）
