Rainfall-runoff model using an artificial neural network approach

被引：147
|
作者：
Riad, S
Mania, J
Bouchaou, L
Najjar, Y
机构：
[1] USTL, LML, EPUL, UMR 8107,CNRS,Ecole Polytech Univ Lille,Dept Geot, F-59655 Villeneuve Dascq, France
[2] Univ Ibn Zohr, Fac Sci, Dept Geol, GAGE, Agadir 80000, Morocco
[3] Kansas State Univ, Dept Civil Engn, Manhattan, KS 66505 USA
来源：
MATHEMATICAL AND COMPUTER MODELLING | 2004年 / 40卷 / 7-8期
关键词：
rainfall-runoff; catchment; semiarid climate; MLP; modelling; artificial neural network; multiple regression; Morocco;
D O I：
10.1016/j.mcm.2004.10.012
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems. In this research, an ANN was developed and used to model the rainfall-runoff relationship, in a catchment located in a semiarid climate in Morocco. The multilayer perceptron (MLP) neural network was chosen for use in the current study. The results and comparative study indicate that the artificial neural network method is more suitable to predict river runoff than classical regression model. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码：839 / 846
页数：8
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