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

Water Resources Management

Volumn 28, Issue 8, 2014, Pages 2109-2128

  Latt, Zaw Zaw ^a   Wittenberg, Hartmut ^a  

^a LEUPHANA UNIVERSITY OF LÜNEBURG   (Germany)

Author keywords

Artificial neural network; Flood forecast; Rainfall; Real time operation; Stepwise regression; Water level

Indexed keywords

DEVELOPING COUNTRIES; FLOOD CONTROL; FORECASTING; NEURAL NETWORKS; RAIN; REAL TIME SYSTEMS; WATER LEVELS;

ARTIFICIAL NEURAL NETWORK MODELS; FLOOD FORECAST; FORECASTING PERFORMANCE; MULTI-STEP FORECASTING; REAL TIME FLOOD FORECASTING; REAL-TIME OPERATION; STEPWISE MULTIPLE LINEAR REGRESSION; STEPWISE REGRESSION;

FLOODS;

ARTIFICIAL NEURAL NETWORK; DEVELOPING WORLD; FLOOD FORECASTING; RAINFALL; REGRESSION ANALYSIS; WATER LEVEL;

CHINDWIN RIVER; MYANMAR;

EID: 84901037108     PISSN: 09204741     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11269-014-0600-8     Document Type: Article

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