摘要
通过用粒子群算法代替混沌序列优化算法的细搜索,可以提高算法的收敛速度及精度。将混沌粒子群混合算法用于分析抽水试验数据,估计各向异性含水层参数,可以有效解决各向异性函数优化问题。与其他算法比较,混沌粒子群混合算法其具有计算精度高、与实测数据拟合效果好及寻优率高等优点。为估计各向异性含水层参数及建立相应的预测和评估模型提供了操作简单、高效且准确的方法。
Using the particle swarm algorithm can increase the convergence speed and precision of the algorithm compared with the optimization search of chaos sequence.The chaos particle swarm algorithm was used to analyze the pumping test data and to estimate the anisotropic aquifer parameters,which can resolve the optimization problems of anisotropy function.Compared with other algorithms,the chaos particle swam algorithm has high calculation precision,fit well with the measured results,and has high optimization rate.This method proves to be simple,efficient,and accurate to estimate anisotropic aquifer parameters and to develop a corresponding prediction and evaluation model.
出处
《南水北调与水利科技》
CAS
CSCD
北大核心
2015年第1期87-90,共4页
South-to-North Water Transfers and Water Science & Technology
基金
国家自然科学基金资助项目(11171043)
关键词
各向异性
含水层参数
参数估计
混沌粒子群混合算法
anisotropy
aquifer parameters
parameter estimation
chaos particle swarm algorithm
