Application of surrogate artificial intelligent models for real-time flood routing

Water and Environment Journal

Volumn 27, Issue 4, 2013, Pages 535-548

  Ghalkhani, Hossein ^a   Golian, Saeed ^b   Saghafian, Bahram ^c   Farokhnia, Ashkan ^a,d   Shamseldin, Asaad ^e  

^a WATER RESEARCH INSTITUTE   (Iran)

^b SHAHROOD UNIVERSITY OF TECHNOLOGY   (Iran)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

^d International Center for Science High Technology and Environmental Sciences   (Iran)

^e UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

Artificial neural networks; Flood routing; Real time; Stability

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ARTIFICIAL INTELLIGENT; COMPUTATIONAL INSTABILITIES; FLOOD ROUTING; HYDRODYNAMIC MODEL; HYDROLOGICAL MODELING; REAL-TIME; REAL-TIME APPLICATION;

COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; FLOOD CONTROL; FLUID DYNAMICS; NEURAL NETWORKS; WATERSHEDS;

FLOODS;

RAIN; SURFACE WATER;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; FLOOD FORECASTING; FLOOD ROUTING; FUZZY MATHEMATICS; HYDRODYNAMICS; HYDROGRAPH; HYDROLOGICAL MODELING; REAL TIME; RIVER BASIN;

ADAPTIVE NEURO FUZZY INFERENCE SYSTEM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; FLOODING; FUZZY SYSTEM; HYDRODYNAMICS; HYDROGRAPHY; PERFORMANCE; PRIORITY JOURNAL; RIVER;

GOLESTAN; IRAN; MADARSOO RIVER;

EID: 84887206471     PISSN: 17476585     EISSN: 17476593     Source Type: Journal    
DOI: 10.1111/j.1747-6593.2012.00344.x     Document Type: Article

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