| 水环境模型参数识别的一种新方法 |
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| 引用本文： | 杨晓华,杨志峰,郦建强.水环境模型参数识别的一种新方法[J].水科学进展,2003,14(5):554-557. |
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| 作者姓名： | 杨晓华 杨志峰 郦建强 |
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| 作者单位： | 1.北京师范大学环境科学研究所, 水环境模拟国家, 重点实验室, 北京, 100875; |
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| 基金项目： | 国家重点基础研究发展规划项目(G1999043605)~~ |
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| 摘 要： | 通过在格雷码遗传算法进化过程中加入单纯形搜索算子,并利用格雷码遗传算法和单纯形法所得到的优秀个体群,作为变量新的变化范围,逐步缩小搜索空间,自动向最优解收缩,提出了水环境模型参数识别的一种新方法——格雷码混合加速遗传算法(GCHAGA),给出了实施该算法的详细步骤。对GCHAGA的收敛性和全局优化性进行了理论和实例分析,并在确定河流横向扩散系数等参数识别问题中,GCHAGA得到了精度较高的全局最优解。与格雷码遗传算法(GCGA)和常规优化方法相比,GCHAGA具有精度高、速度快和适用性强等特点,是一种既可以较大概率搜索全局最优解,又能进行局部细致搜索的较好的非线性优化方法,可广泛应用于各种水环境优化问题中。
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| 关 键 词： | 格雷码 遗传算法 精度 水环境模型 参数识别 |
| 文章编号： | 1001-6791(2003)05-554-04 |
| 收稿时间： | 2002-07-19 |
| 修稿时间： | 2002年7月19日 |
A new method for parameter identification in water environment model |
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| YANG Xiao-hua,YANG Zhi-feng,LI Jian-qiang.A new method for parameter identification in water environment model[J].Advances in Water Science,2003,14(5):554-557. |
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| Authors: | YANG Xiao-hua YANG Zhi-feng LI Jian-qiang |
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| Affiliation: | 1.Institute of Environmental Sciences, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China;2.Institute of Water Sciences, Key Laboratory for Water and Sediment Sciences Ministry of Education, Beijing Normal University, Beijing 100875, China;3.Water Resources and Hydropower Planning and Design General Institute, MWR, Beijing 10001, China |
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| Abstract: | In this study,a new method,Gray Code Hybrid Accelerating Genetic Algorithm (GCHAGA),and its detailed steps are developed to identify water environment model parameters.With the shrinking of searching range,the method gradually directs to optimal result by the excellent individuals obtained by gray code genetic algorithm (GCGA) embedding with simplex searching operator and simplex algorithm.Further,the convergence and global optimization of the GCHAGA is discussed theoretically and practically,and its high precision on global optimization is ascertained over such parameters as river transverse diffuse coefficients model.Compared with the GCGA and the conventional optimization methods,the GCHAGA remarkably improves convergence speed and calculation accuracy.It proves a good nonlinear optimal method that can search both global solution and fractional one in greater probability,and could be applied to various water environment optimization issues. |
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| Keywords: | Gray code genetic algorithm precision water environment model parameter identification |
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