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基于模糊聚类和BP神经网络的流域洪水分类预报研究
引用本文:任明磊,王本德. 基于模糊聚类和BP神经网络的流域洪水分类预报研究[J]. 大连理工大学学报, 2009, 49(1): 121-127
作者姓名:任明磊  王本德
作者单位:大连理工大学土木水利学院,辽宁大连,116024;大连理工大学土木水利学院,辽宁大连,116024
基金项目:国家自然科学基金资助项目(50479056)
摘    要:
传统的流域洪水预报大都通过率定一组水文模型参数来寻求一个流域径流形成的一般性或平均化规律,其预报精度需要进一步提高.用模糊聚类ISODATA迭代模型将历史洪水分为若干类型,进行水文预报模型参数的分类调试;并建立BP神经网络分类模型判断实时洪水所属类别,选择其相应类别的模型参数实现流域洪水的分类预报.在辽宁省大伙房水库流域的实际应用表明:此方法不但可以实现洪水实时在线分类而且提高了流域整体洪水预报精度,是一种为水库实时调度提供可靠依据的有效洪水预报方法.

关 键 词:洪水预报  分类  BP神经网络  模糊聚类

Research on classified flood forecast based on fuzzy clustering and BP neural networks
REN Minglei,WANG Bende. Research on classified flood forecast based on fuzzy clustering and BP neural networks[J]. Journal of Dalian University of Technology, 2009, 49(1): 121-127
Authors:REN Minglei  WANG Bende
Affiliation:REN Ming-lei,WANG Ben-de School of Civil , Hydraulic Engineering,Dalian University of Technology,Dalian 116024,China
Abstract:
Traditional flood forecast usually tries to find the generic or average disciplinarian of forming runoff in the basin by rating a set of hydrological model parameters,and its forecasting precision needs to be further improved.Firstly,the historical floods were divided into several types by fuzzy clustering ISODATA iterative model,and several sets of hydrological model parameters were debugged separately.Secondly,BP neural networks classified model was established to judge the category of real-time flood,and...
Keywords:flood forecast  classification  BP neural networks  fuzzy clustering  
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