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基于Elman型回馈神经网络的流域降雨-径流动态过程建模的研究
引用本文:梅松,程伟平,刘国华. 基于Elman型回馈神经网络的流域降雨-径流动态过程建模的研究[J]. 水力发电学报, 2004, 23(3): 31-35
作者姓名:梅松  程伟平  刘国华
作者单位:浙江大学建筑工程学院,杭州,310027;浙江大学建筑工程学院,杭州,310027;浙江大学建筑工程学院,杭州,310027
摘    要:本文将Elman回馈型神经网络与水文系统的特点相结合 ,建立了流域降雨 -径流动态模型。文中用较简单的方法解决了神经网络模型难以直接描述水文系统前期状态的难题 ,并以福建沙县流域的降雨 -径流过程为研究对象 ,通过完整的分析 ,表明Elman型神经网络与水文系统概念相结合的动态过程模型是一种能够保证较高的预报准确性的模型 ,同时又具有良好的适应性、健壮型和外延性 ,显示出良好的应用前景。

关 键 词:洪水预报  动态建模  Elman型回馈神经网络  降雨-径流
修稿时间:2003-04-25

Case study of rainfall-runoff dynamic model using Elman recurrent artificial neural networks
MEI Song,CHENG Weiping,LIU Guohua. Case study of rainfall-runoff dynamic model using Elman recurrent artificial neural networks[J]. Journal of Hydroelectric Engineering, 2004, 23(3): 31-35
Authors:MEI Song  CHENG Weiping  LIU Guohua
Abstract:A dynamic rainfall-runoff model was established in consideration of the characteristic combination of Elman recurrent artificial neural networks and the hydrology system.In this paper,the difficult problem of describing the forepart state of hydrology system by neural networks mode was solved by relatively simple method.Case study and analysis of the rainfall-runoff process of Shaxi basin in Fujian province is expressed that the dynamic process model in consideration of combination with Elman neural networks and the hydrology system is one of the flexible,extendable model with high accuracy of forecast,it assumes the bright aspect of this mode application.
Keywords:flood forecast  dynamic model  Elman recurrent neural networks  rainfall-runoff model
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