期刊文献+

概念性水文模型遗传算法多目标参数优选研究 被引量:4

Study on optimization of multi-objective parameter of genetic algorithm for conceptual hydrological model
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摘要 简要介绍了概念性降水—径流模型的多目标参数优选方法,以新安江模型为例,从Pareto支配法(Pareto Domination Approach)原理出发讨论了四目标函数情形下Pareto最优参数空间(Pareto Optimal Set)的Pareto优先排序(Pareto Preference Ordering)求解策略。通过对汉江上游江口流域降水—径流的新安江模型的模拟检验,证明该方法能够为模型提供全局最优参数,好于传统的单目标参数优选结果。 The optimization method of multi-objective parameter for the conceptual rainfall-runoff hydrological simulations is briefly introduced; and then by taking the hydrological simulation with Xinanjiang model as an example, the Pareto Preference Ordering solution for parameter space of Pareto optimal set under four-objective function condition is discussed herein from the view- point of Pareto Domination Approach principles. Through the rainfall-runoff simulations made with Xinanjiang model for the Jiangkou Watershed on upstream of Hanjiang River, it is demonstrated that the proposed methodology can effectively provide the globally optimized parameters for the model, and the results are superior to the results from the single objective parameter optimization.
出处 《水利水电技术》 CSCD 北大核心 2007年第6期5-7,11,共4页 Water Resources and Hydropower Engineering
基金 国家重点基础研究发展规划项目(2006CB400502及2001CB309404) 中科院"百人计划"择优支持项目(8-057493) 中科院大气物理所东亚区域气候-环境重点实验室开放基金资助
关键词 Pareto支配法 Pareto优先排序算法 遗传算法 参数优选 新安江模型 Pareto domination approach Pareto preference ordering Genetic algorithm parameter optimization Xinanjiang model
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参考文献11

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二级参考文献13

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