DOI: 10.1007/s11069-020-04211-5
论文题名: Flood forecasting based on an artificial neural network scheme
作者: Dtissibe F.Y. ; Ari A.A.A. ; Titouna C. ; Thiare O. ; Gueroui A.M.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 104, 期: 2 起始页码: 1211
结束页码: 1237
语种: 英语
中文关键词: Artificial neural networks
; Flood forecasting
; Machine learning
; Multilayer perceptron
英文关键词: artificial neural network
; discharge
; experimental study
; flood forecasting
; input-output analysis
; machine learning
; numerical model
; perception
英文摘要: Nowadays, floods have become the widest global environmental and economic hazard in many countries, causing huge loss of lives and materials damages. It is, therefore, necessary to build an efficient flood forecasting system. The physical-based flood forecasting methods have indeed proven to be limited and ineffective. In most cases, they are only applicable under certain conditions. Indeed, some methods do not take into account all the parameters involved in the flood modeling, and these parameters can vary along a channel, which results in obtaining forecasted discharges very different from observed discharges. While using machine learning tools, especially artificial neural networks schemes appears to be an alternative. However, the performance of forecasting models, as well as a minimum error of prediction, is very interesting and challenging issues. In this paper, we used the multilayer perceptron in order to design a flood forecasting model and used discharge as input–output variables. The designed model has been tested upon intensive experiments and the results showed the effectiveness of our proposal with a good forecasting capacity. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168471
Appears in Collections: 气候变化与战略
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作者单位: LI-PaRAD Lab, Université Paris Saclay, University of Versailles Saint-Quentin-en-Yvelines, 45 Avenue des États-Unis, Versailles Cedex, 78035, France; LaRI Lab, University of Maroua, Maroua, P.O. Box 814, Cameroon; LANI Lab, Gaston Berger University of Saint-Louis, Saint-Louis, P.O. Box 234, Senegal; LIPADE Lab, University of Paris, 45 Rue des Saints Pères, Paris, 75006, France
Recommended Citation:
Dtissibe F.Y.,Ari A.A.A.,Titouna C.,et al. Flood forecasting based on an artificial neural network scheme[J]. Natural Hazards,2020-01-01,104(2)