Application of neural network and adaptive neuro-fuzzy inference systems for river flow prediction

Hydrological Sciences Journal

Volumn 54, Issue 2, 2009, Pages 247-260

  Pramanik, Niranjan ^a   Panda, Rabindra Kumar ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Fuzzy inference system; Hydrological processes; Neural networks; Training algorithms

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ARTIFICIAL INTELLIGENCE TECHNIQUES; ARTIFICIAL NEURAL NETWORK; CONJUGATE GRADIENT ALGORITHMS; CORRELATION COEFFICIENT; DOWNSTREAM REGION; FEEDFORWARD BACKPROPAGATION; FLOW DATA; FUZZY INFERENCE SYSTEM; GRADIENT DESCENT ALGORITHMS; HYDROLOGICAL PROCESS; HYDROLOGICAL PROCESSES; INDEX OF AGREEMENTS; INPUT-OUTPUT MAPPING; LEVENBERG-MARQUARDT; MAHANADI RIVER BASIN; PEAK FLOWS; PERCENTAGE DEVIATION; PHYSICALLY BASED MODELS; RAINY SEASONS; RIVER FLOW PREDICTION; ROOT MEAN SQUARE ERRORS; STANDARD PERFORMANCE; TIME STEP; TRAINING ALGORITHMS; TRAINING TECHNIQUES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CONJUGATE GRADIENT METHOD; DAMS; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; RESERVOIRS (WATER); TRACKING (POSITION);

RIVERS;

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; BARRAGE; FUZZY MATHEMATICS; NUMERICAL MODEL; OUTFLOW; PREDICTION; RIVER FLOW;

ASIA; EURASIA; INDIA; MAHANADI RIVER; SOUTH ASIA;

EID: 69949143939     PISSN: 02626667     EISSN: None     Source Type: Journal    
DOI: 10.1623/hysj.54.2.247     Document Type: Article

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