Comparison of data-driven modelling techniques for river flow forecasting;Comparaison de techniques de modélisation conditionnée par les données pour la prévision des débits fluviaux

Hydrological Sciences Journal

Volumn 55, Issue 7, 2010, Pages 1163-1174

  Londhe, Shreenivas ^a   Charhate, Shrikant ^b  

^a VISHWAKARMA INSTITUTE OF INFORMATION TECHNOLOGY   (India)

^b Datta Meghe College of Engineering   (India)

Author keywords

Artificial neural networks; Data driven modelling; Genetic programming; M5 model trees; Streamflow

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CONCEPTUAL MODEL; DATA-DRIVEN; EXTREME EVENTS; HIGHLY NONLINEAR; M5 MODEL TREE; MODEL TREES; MODELLING TECHNIQUES; PREDICTION ACCURACY; REASONABLE ACCURACY; RIVER FLOW; RIVER FLOW FORECASTING; WATER RESOURCES SYSTEMS;

CATCHMENTS; FORECASTING; GENETIC PROGRAMMING; STREAM FLOW; TREES (MATHEMATICS); WATER RESOURCES;

NEURAL NETWORKS;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; BASIN ANALYSIS; CATCHMENT; COMPARATIVE STUDY; LINEAR PROGRAMING; NONLINEARITY; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; PREDICTION; RIVER BASIN; RIVER FLOW; STREAMFLOW;

INDIA; NARMADA BASIN;

EID: 78650509451     PISSN: 02626667     EISSN: 21503435     Source Type: Journal    
DOI: 10.1080/02626667.2010.512867     Document Type: Article

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