TVP

# 确定越流含水层参数的混沌序列优化算法

1长安大学 环境科学与工程学院,西安 710054

2. 旱区地下水文与生态效应教育部重点实验室,西安 710054

Chaotic time-series optimization algorithm for leakage aquifer parameters estimation

Based on the analytical solution to well flow problem of unsteady flows in the first type leakage aquifer, the chaotic time-series optimization algorithm is employed to analyze the data of pumpling tests to determine aquifer parameters. Numerical simulation is conducted through analysis of the influence of the initial value of aquifer parameters and other factors on the convergence and results of the algorithm. The results show that:①chaotic time-series optimization algorithm can be effectively applied to the calculation problem of aquifer parameters; ②the initial value of leakage factor and the coefficient of storage and conductivity don’t have too much obvious effect on the search and results of the algorithm，except reduce the accurancy of results of leakage factor due to its initial value. Compared with other methods, the chaotic optimization method has such advantages as simple in principle of algorithm, easy to make program and to conduct, and the precision of aquifer parameters calculated is not affected by artificial subjective factors.

Key words

chaotic time-series optimization algorithm, leakage system, leakage factor

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（１） 函数粗搜索收敛值和细搜索收敛值要足够小并且越接近越好；

（２） 选定混沌序列长度在１００～６００之间、 粗搜索次数在２～２０之间对本案例较为适合；

（３） 算法的收敛性不受待估含水层参数初值范围的影响， 鉴于越流因数对搜索结果的影响， 含水层各参数初值范围应尽量与待估参数参考值接近。所以， 对于分析第一类越流系统含水层抽水试验、 确定含水层参数的问题， 混沌序列优化算法是一种新的选择。

• 发表于:
• 原文链接https://kuaibao.qq.com/s/20180706B1RL8K00?refer=cp_1026
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