Efficacy of neural network and genetic algorithm techniques in simulating spatio-temporal fluctuations of groundwater

Hydrological Processes

Volumn 29, Issue 5, 2015, Pages 671-691

  Jha, Madan K ^a   Sahoo, Sasmita ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Alluvial aquifer system; Artificial neural network (ANN); Genetic algorithm; Groundwater level prediction; Model evaluation criteria; Uncertainty analysis

Indexed keywords

AQUIFERS; ERROR STATISTICS; FORECASTING; GENETIC ALGORITHMS; GROUNDWATER; MEAN SQUARE ERROR; MULTILAYER NEURAL NETWORKS; NEURAL NETWORKS; PREDICTIVE ANALYTICS; UNCERTAINTY ANALYSIS;

ALLUVIAL AQUIFER SYSTEMS; GOODNESS-OF-FIT STATISTICS; GROUNDWATER UTILIZATION; HYBRID ARTIFICIAL NEURAL NETWORK; MODEL EVALUATION; RADIAL BASIS FUNCTION MODELS; ROOT MEAN SQUARED ERRORS; SPATIO-TEMPORAL FLUCTUATIONS;

GROUNDWATER RESOURCES;

EID: 84924634673     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.10166     Document Type: Article

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