Determination of input for artificial neural networks for flood forecasting using the copula entropy method

Journal of Hydrologic Engineering

Volumn 19, Issue 11, 2014, Pages

  Chen, Lu ^a   Ye, Lei ^a   Singh, Vijay ^b   Zhou, Jianzhong ^a   Guo, Shenglian ^c  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b Texas A M University   (United States)

^c WUHAN UNIVERSITY   (China)

Author keywords

Artificial neural networks; Copula entropy; Flood forecasting; Input variables selection; Partial mutual information(PMI)

Indexed keywords

CORRELATION THEORY; FLOOD CONTROL; FLOODS; MEAN SQUARE ERROR; PROBABILITY DISTRIBUTIONS; RESERVOIRS (WATER); WEATHER FORECASTING;

FLOOD FORECASTING; FLOOD FORECASTING MODELS; HYDROLOGICAL MODELING; INPUT VARIABLES SELECTIONS; JOINT PROBABILITY DISTRIBUTIONS; PARTIAL MUTUAL INFORMATIONS; ROOT MEAN SQUARE ERRORS; THREE GORGES RESERVOIR;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; FLOOD FORECASTING; HYDROLOGICAL MODELING; PROBABILITY; STATISTICAL DISTRIBUTION;

CHINA; THREE GORGES RESERVOIR; YANGTZE RIVER;

EID: 84911877928     PISSN: 10840699     EISSN: 19435584     Source Type: Journal    
DOI: 10.1061/(ASCE)HE.1943-5584.0000932     Document Type: Article

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