Improving Flood Forecasting in a Developing Country: A Comparative Study of Stepwise Multiple Linear Regression and Artificial Neural Network

Due to limited data sources, practical situations in most developing countries favor black-box models in real time operations. In a simple and robust approach, this study examines performances of stepwise multiple linear regression (SMLR) and artificial neural network (ANN) models, as tools for mult...

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Veröffentlicht in:	Water resources management 2014-06, Vol.28 (8), p.2109-2128
Hauptverfasser:	Latt, Zaw Zaw, Wittenberg, Hartmut
Format:	Artikel
Sprache:	eng
Schlagworte:	Atmospheric Sciences Civil Engineering Comparative studies Correlation analysis Developing countries Earth and Environmental Science Earth Sciences Earth, ocean, space Engineering and environment geology. Geothermics Environment Exact sciences and technology Flood forecasting Floods Forecasting Forecasting techniques Freshwater Geotechnical Engineering & Applied Earth Sciences Hydrogeology Hydrology Hydrology. Hydrogeology Hydrology/Water Resources LDCs Learning theory linear models Mathematical models model validation Natural hazards: prediction, damages, etc Neural networks prediction Rain Regression Regression analysis Rivers Stations Studies Upstream Water levels Water resources
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