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水质模型的参数优化:遗传算法的实现及其控制参数分析

[Parameter optimization of water quality model: implementation of genetic algorithm and its control parameters analysis].

作者信息

Wang Jian-ping, Cheng Sheng-tong, Jia Hai-feng

机构信息

Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084, China.

出版信息

Huan Jing Ke Xue. 2005 May;26(3):61-5.

Abstract

Parameter identification plays an important role in environmental model application. As a commonly used global optimization method, genetic algorithm (GA) has very simple structure, the key related to whether a practical issue can be solved using GA or not is algorithm design and selection of the control parameters. Based on the feature of parameter optimization of water quality model, orthogonal test method was proposed for reviewing effects of different control parameters of GA on the performance of water quality parameter optimization. The results indicate that orthogonal method could identify key factors, and also provide possible optimized experiment plan. It is concluded that GA can be applied to the research on parameter identification of complicated water quality model.

摘要

参数识别在环境模型应用中起着重要作用。作为一种常用的全局优化方法,遗传算法(GA)结构非常简单,能否使用遗传算法解决实际问题的关键在于算法设计和控制参数的选择。基于水质模型参数优化的特点,提出了正交试验法来考察遗传算法不同控制参数对水质参数优化性能的影响。结果表明,正交试验法能够识别关键因素,还能提供可能的优化试验方案。得出遗传算法可应用于复杂水质模型参数识别研究的结论。

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