Daily reservoir inflow forecasting using artificial neural networks with stopped training approach

Journal of Hydrology

Volumn 230, Issue 3-4, 2000, Pages 244-257

  Coulibaly, P ^a   Anctil, F ^a   Bobee B ^b  

^a UNIVERSITÉ LAVAL   (Canada)

^b HYDRO QUÉBEC   (Canada)

Author keywords

Artificial neural networks; Real time forecasting; Reservoir inflow; Stopped training approach

Indexed keywords

BACKPROPAGATION; FEEDFORWARD NEURAL NETWORKS; MATHEMATICAL MODELS; MULTILAYER NEURAL NETWORKS; REAL TIME SYSTEMS; STATISTICAL METHODS; TIME SERIES ANALYSIS;

CROSS-VALIDATION METHOD; LEVENBERG-MARQUARDT BACKPROPAGATION (LMBP); MULTIVARIATE HYDROLOGICAL TIME SERIES ANALYSIS; RESERVOIR INFLOW; STOPPED TRAINING METHODS;

RESERVOIRS (WATER);

ARTIFICIAL NEURAL NETWORK; FORECASTING METHOD; INFLOW; RESERVOIR;

EID: 0034621379     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0022-1694(00)00214-6     Document Type: Article

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