基于混沌人工鱼群混合算法确定含水层参数  

Aquifer Parameter Estimation Based on Chaos Artificial Fish Swarm Combined Algorithms

作　　者：王静云[1] 常安定[1] 郭建青[2] 周秀秀[1] 

机构地区：[1]长安大学理学院,西安710064 [2]长安大学环境科学与工程学院,西安710051

出　　处：《中国农村水利水电》2013年第3期27-29,33,共4页China Rural Water and Hydropower

基　　金：中央高校基本科研业务费专项资金(CHD2012TD015)

摘　　要：以泰斯公式为基础,将混沌人工鱼群混合算法应用于求解分析抽水试验资料,确定含水层参数的函数优化问题。人工鱼群算法是一种群智能全局随机优化算法,收敛速度快,但存在早熟收敛现象;混沌序列具有遍历性和随机性等特点。为此将混沌系统与人工鱼群算法结合,构造了混沌人工鱼群混合算法。数值实验结果表明:混沌人工鱼群混合算法能成功用于确定含水层参数的函数优化问题,且与人工鱼群算法相比较具有收敛快、效率高和结果精度高等优点,从而为确定含水层参数提供了一种新方法。The chaos artificial fish swarm combined algorithm is applied to analyze the pumping experiment data to optimize the func tion of aquifer parameters to estimate the parameters based on Tahis Equation. Artificial fish swarm optimization is a swarm intelli gence stochastic global optimization algorithm, but there is the defect of premature convergence. Chaotic time-series possesses the feature of ergodicity and randomness. So we combined artificial fish swarm optimization algorithm and chaos forming a new fusion optimization algorithm-chaos artificial fish swarm combined algorithm（CAFSA）. The numerical experiment results show that CAFSA can be successfully applied in aquifer parameter estimation, compared with AFSA, CAFSA has the advantage of rapid convergence rate, high optimization efficiency and high accuracy. So a new way for aquifer parameter estimation is provided.

关 键 词：参数计算 抽水试验资料 水文地质参数 混沌寻优 人工鱼群优化 混合算法 

分 类 号：TV211.12[水利工程—水文学及水资源]