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Rainfall-runoff model usingan artificial neural network approach
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 p...
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Published in: | Mathematical and computer modelling 2004, Vol.40 (7-8), p.839-846 |
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container_title | Mathematical and computer modelling |
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creator | Riad, Souad Mania, Jacky Bouchaou, L. Najjar, Y. |
description | 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. |
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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.</description><identifier>ISSN: 0895-7177</identifier><language>eng</language><publisher>Elsevier</publisher><ispartof>Mathematical and computer modelling, 2004, Vol.40 (7-8), p.839-846</ispartof><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,4022</link.rule.ids><backlink>$$Uhttps://hal.science/hal-00138173$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Riad, Souad</creatorcontrib><creatorcontrib>Mania, Jacky</creatorcontrib><creatorcontrib>Bouchaou, L.</creatorcontrib><creatorcontrib>Najjar, Y.</creatorcontrib><title>Rainfall-runoff model usingan artificial neural network approach</title><title>Mathematical and computer modelling</title><description>The use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems. 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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.</abstract><pub>Elsevier</pub></addata></record> |
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title | Rainfall-runoff model usingan artificial neural network approach |
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