Enhancing the predicting accuracy of the water stage using a physical-based model and an artificial neural network-genetic algorithm in a river system

Water (Switzerland)

Volumn 6, Issue 6, 2014, Pages 1642-1661

  Liu, Wen Cheng ^a,b   Chung, Chuan En ^a  

^a NATIONAL UNITED UNIVERSITY   (Taiwan)

^b NATIONAL APPLIED RESEARCH LABORATORIES   (Taiwan)

Author keywords

Back propagation neural network; Danshuei river system; Flood routing hydrodynamic model; Genetic algorithm neural network; Model calibration (training) and verification; Water stage

Indexed keywords

ALGORITHMS; BOUNDARY CONDITIONS; COMPUTER SIMULATION; DISASTER PREVENTION; FLOOD CONTROL; FLOODS; FLUID DYNAMICS; GENETIC ALGORITHMS; HURRICANES; NEURAL NETWORKS; WATER LEVELS; WATER RESOURCES;

ARTIFICIAL NEURAL NETWORK MODELS; BACK PROPAGATION NEURAL NETWORKS; HYDRODYNAMIC MODEL; MODEL CALIBRATION; MODEL CALIBRATION AND VERIFICATION; PHYSICAL BASED MODELING; RIVER SYSTEMS; WATER RESOURCES MANAGEMENT;

RIVERS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BOUNDARY CONDITION; FLOOD CONTROL; HYDROLOGICAL MODELING; NUMERICAL MODEL; RIVER SYSTEM; SIMULATION; TYPHOON; WATER LEVEL;

DANSHUI RIVER; TAIWAN;

EID: 84902007521     PISSN: None     EISSN: 20734441     Source Type: Journal    
DOI: 10.3390/w6061642     Document Type: Article

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