A hybrid model of self organizing maps and least square support vector machine for river flow forecasting

Hydrology and Earth System Sciences

Volumn 16, Issue 11, 2012, Pages 4417-4433

  Ismail, S ^a   Shabri, A ^a   Samsudin, R ^b  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; FORECASTING TECHNIQUES; HIGH-DIMENSIONAL; HYBRID MODEL; INPUT PATTERNS; INPUT SPACE; LEAST SQUARE SUPPORT VECTOR MACHINES; LEAST SQUARES SUPPORT VECTOR MACHINES; LOW DIMENSIONAL; MALAYSIA; OUTPUT LAYER; PERFORMANCE INDICATORS; RIVER FLOW; RIVER FLOW FORECASTING; SOM ALGORITHMS; WATER RESOURCE PLANNING;

BENCHMARKING; SELF ORGANIZING MAPS; STREAM FLOW; WATER RESOURCES;

FORECASTING;

ARTIFICIAL NEURAL NETWORK; DATA SET; EXPERIMENTAL STUDY; FEASIBILITY STUDY; FORECASTING METHOD; HYDROLOGICAL MODELING; LEAST SQUARES METHOD; PERFORMANCE ASSESSMENT; RIVER FLOW; WATER MANAGEMENT; WATER PLANNING; WATER RESOURCE;

BERNAM RIVER; MALAYSIA; SELANGOR; WEST MALAYSIA;

EID: 84870283667     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-16-4417-2012     Document Type: Article

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