Improving the forecasts of extreme streamflow by support vector regression with the data extracted by self-organizing map

Hydrological Processes

Volumn 28, Issue 2, 2014, Pages 386-397

  Wu, Ming Chang ^a,b   Lin, Gwo Fong ^a   Lin, Hsuan Yu ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b NATIONAL APPLIED RESEARCH LABORATORIES   (Taiwan)

Author keywords

Extreme events; Flood warning system; Self organizing map; Streamflow forecasting; Support vector machine

Indexed keywords

COMPLEX PHYSICAL PROCESS; COMPUTATIONAL KERNELS; EXTREME EVENTS; FLOOD WARNING SYSTEM; FORECASTING PERFORMANCE; SPECIFIC PROPERTIES; STREAMFLOW FORECASTING; SUPPORT VECTOR REGRESSION (SVR);

ALARM SYSTEMS; CONFORMAL MAPPING; FLOODS; GLOBAL WARMING; SELF ORGANIZING MAPS; STREAM FLOW; SUPPORT VECTOR MACHINES;

FORECASTING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; ERROR ANALYSIS; EXTREME EVENT; FLOOD; FORECASTING METHOD; GLOBAL WARMING; HYDROLOGICAL MODELING; STREAMFLOW; WARNING SYSTEM;

EID: 84891559585     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.9584     Document Type: Article

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