Integrating Support Vector Regression and a geomorphologic Artificial Neural Network for daily rainfall-runoff modeling
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- 作者：Seiyed Mossa Hosseinia ; smhosseini@ut.ac.ir" class="auth_mail" title="E-mail the corresponding author ; Najmeh Mahjourib ; mahjouri@kntu.ac.ir" class="auth_mail" title="E-mail the corresponding author
- 关键词：Rainfall-runoff modeling ; Geomorphologic characteristics ; Support Vector Regression (SVR) ; Artificial Neural Networks (ANNs) ; Genetic algorithm ; Fuzzy inference system (FIS)
- 刊名：Applied Soft Computing
- 出版年：2016
- 出版时间：January 2016
- 年：2016
- 卷：38
- 期：Complete
- 页码：329-345
- 全文大小：4918 K
文摘
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A SVR model based on a geomorphologic-ANN model is developed to estimate the runoff.
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The results of the SVR-GANN model are assessed from modeling viewpoints.
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Equipping the SVR model with ANN as kernel function has improved the model accuracy.
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The SVR-GANN model can be applied as a promising tool for rainfall-runoff modeling.