Simulation of river stage using artificial neural network and MIKE 11 hydrodynamic model

Computers and Geosciences

Volumn 36, Issue 6, 2010, Pages 735-745

  Panda, Rabindra K ^a   Pramanik, Niranjan ^a   Bala, Biplab ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Artificial neural network; Back propagation training algorithms; Hydrodynamic model; LM algorithm

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CHANNEL ROUGHNESS; CONTROL STRUCTURE; FLOOD ROUTING; GOODNESS OF FIT; HIDDEN LAYERS; HIDDEN NEURONS; HYDRODYNAMIC MODEL; HYDROLOGIC SIMULATIONS; HYDROLOGIC TIME SERIES; LEVENBERG-MARQUARDT; LEVENBERG-MARQUARDT ALGORITHM; LM ALGORITHM; MODEL TESTING; MODEL VALIDATION; NEURAL NETWORK MODEL; PHYSICALLY BASED; RECORD KEEPING; RIVER GEOMETRY; ROOT MEAN SQUARE ERRORS; TRAINING ALGORITHMS; WATER-LEVEL DATA;

ALGORITHMS; BACKPROPAGATION; DATA FLOW ANALYSIS; DEVELOPING COUNTRIES; FLOOD CONTROL; FLUID DYNAMICS; HYDRODYNAMICS; LAGRANGE MULTIPLIERS; MATHEMATICAL MODELS; NEURAL NETWORKS; RIVER CONTROL; TIME SERIES; WATER LEVELS;

COMPUTER SIMULATION;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; FLOOD ROUTING; HYDRODYNAMICS; RIVER FLOW; SIMULATION; WATER LEVEL;

EID: 77953122265     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2009.07.012     Document Type: Article

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