A novel nonlinear combination model based on support vector machine for rainfall prediction

Proceedings - 4th International Joint Conference on Computational Sciences and Optimization, CSO 2011

Volumn , Issue , 2011, Pages 1343-1346

  Lu, Kesheng ^a   Wang, Lingzhi ^b  

^a GUANGXI NORMAL UNIVERSITY FOR NATIONALITIES   (China)

^b Liuzhou Teachers College ^*  (China)

Author keywords

Kernel function; Partial least square; Rainfall prediction; Support vector machine

Indexed keywords

BASE MODELS; COMBINATION MODELS; EMPIRICAL RESULTS; FORECASTING ACCURACY; FORECASTING TOOLS; GUANGXI; KERNEL FUNCTION; NONLINEAR COMBINATION; NONLINEAR ENSEMBLE MODEL; PARTIAL LEAST SQUARES; PREDICTION QUALITY; RAINFALL PREDICTION; SAMPLING TECHNIQUE; SUPPORT VECTOR; TRAINING SETS;

OPTIMIZATION; SUPPORT VECTOR MACHINES; WEATHER FORECASTING;

RAIN;

EID: 80051993442     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSO.2011.50     Document Type: Conference Paper

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