| 王建平,程声通.遗传单纯形混合算法在复杂环境模型参数识别中的应用[J].水利学报,2005,36(6):0674-0679 |
| 遗传单纯形混合算法在复杂环境模型参数识别中的应用 |
| Application of genetic algorithm and simplex method in parameter identification of complicated environmental model |
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| DOI： |
| 中文关键词: 参数识别 环境模型 遗传算法 单纯形法 全局优化 混合算法 |
| 英文关键词: parameter identification environmental model genetic algorithm simplex method global optimization hy brid Algoribhms |
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| 中文摘要: |
| 参数识别是数学模型应用的一个重要环节。为提高复杂环境模型参数识别的性能和效率，引入了遗传单纯形法(GASM)，该方法融合了遗传算法和单纯形法两类算法的不同搜索机制，具有很强的广度搜索和深度搜索能力。本研究以密云水库水质模拟为例，将GASM算法应用于模拟地表水水质的WASP模型中10个参数的优化识别。计算结果表明，无论是没有扰动的情况还是有扰动的情况，GASM算法均高效可靠地搜索到水质模型参数的全局最优解，说明此方法应用于复杂环境模型参数搜索是可行的实用的。同时，通过不同算法的比较也说明了GASM算法在搜索性能和效率方面的优越性。 |
| 英文摘要: |
| Parameter identification plays an important role in application of mathematical model. In order to improve the performance and efficiency of parameter identification in complicated environmental models, the genetic algorithm and simplex method (GASM) are introduced. This hybrid method integrates the search mechanisms of these two methods and greatly elevates the ability of exploration and exploitation. The simulation of water quality in the Miyun Reservoir is presented as an example to demonstrate the application of this method. The optimal identification of 10 parameters in the model simulating the surface water quality (WASP) is carried out. The calculation result indicates that the global optimized solutions of these parameters can be reliably and effectively acquired either in the condition of non-disturbed data or in the condition of disturbed data. The comparisons among different optimization methods also show that GASM possesses particular advantages in performance and efficiency. |
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