River flow time series using least squares support vector machines

Hydrology and Earth System Sciences

Volumn 15, Issue 6, 2011, Pages 1835-1852

  Samsudin, R ^a   Saad, P ^a   Shabri, A ^a  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

Author keywords

[No Author keywords available]

Indexed keywords

AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE; COEFFICIENT OF CORRELATION; CONVENTIONAL ARTIFICIAL NEURAL NETWORK MODELS; FLOW FORECASTS; GROUP METHOD OF DATA HANDLING; HYBRID FORECASTING; HYBRID MODEL; INPUT VARIABLES; LEAST SQUARES SUPPORT VECTOR MACHINES; LONG TERM OBSERVATIONS; MALAYSIA; RIVER FLOW; RIVER FLOW DISCHARGES; RIVER FLOW FORECASTING; RIVER FLOW TIME SERIES; ROOT MEAN SQUARE ERRORS; TIME SERIES FORECASTING;

DATA HANDLING; FORECASTING; MEAN SQUARE ERROR; NEURAL NETWORKS; TIME SERIES;

STREAM FLOW;

ARTIFICIAL NEURAL NETWORK; DATA SET; FORECASTING METHOD; NUMERICAL MODEL; RIVER DISCHARGE; RIVER FLOW; TIME SERIES;

BERNAM RIVER; MALAYSIA; SELANGOR; SELANGOR RIVER; WEST MALAYSIA;

EID: 84872725276     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-15-1835-2011     Document Type: Article

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