A new hybrid artificial neural networks for rainfall-runoff process modeling

Neurocomputing

Volumn 121, Issue , 2013, Pages 470-480

  Asadi, Shahrokh ^a   Shahrabi, Jamal ^a   Abbaszadeh, Peyman ^a   Tabanmehr, Shabnam ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Data clustering; Data pre processing; Genetic algorithms; Levenberg Marquardt algorithm; Rainfall runoff modeling

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; DATA CLUSTERING; DATA PREPROCESSING; HYBRID ARTIFICIAL NEURAL NETWORK; HYBRID INTELLIGENT MODEL; INPUT VARIABLES SELECTIONS; LEVENBERG-MARQUARDT ALGORITHM; RAINFALL-RUNOFF MODELING;

CLUSTERING ALGORITHMS; CORRELATION THEORY; FORECASTING; GENETIC ALGORITHMS; RAIN; RUNOFF;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AZERBAIJAN; CONTROLLED STUDY; DATA PROCESSING; GENETIC ALGORITHM; IRAN; LEVENBERG MARQUARDT ALGORITHM; PRE PROCESSED EVOLUTIONARY LEVENBERG MARQUARDT NEURAL NETWORK; PREDICTION AND FORECASTING; PRIORITY JOURNAL; PROCESS MODEL; RAINFALL RUNOFF PROCESS MODELING; WATERSHED;

EID: 84884167501     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.05.023     Document Type: Article

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