A hybrid model for short-term wind speed forecasting based on ensemble empirical mode decomposition and least squares support vector machines

Diangong Jishu Xuebao/Transactions of China Electrotechnical Society

Volumn 29, Issue 4, 2014, Pages 237-245

  Wang, He ^a   Hu, Zhijian ^a   Zhang, Yihui ^b   Li, Chen ^a   Yang, Nan ^a   Wang, Zhansheng ^c  

^a WUHAN UNIVERSITY   (China)

^b Guang Xi Electric Power Research Institute   (China)

^c Xinxiang Power Supply Company   (China)

Author keywords

Adaptive disturbance particle swarm optimization; Ensemble empirical mode decomposition(EEMD); Forecasting; Learning effect feedback; Least squares support vector machines; Wind speed

Indexed keywords

PARTICLE SWARM OPTIMIZATION (PSO); WIND;

COMBINATION FORECASTING MODELS; ENSEMBLE EMPIRICAL MODE DECOMPOSITION; ENSEMBLE EMPIRICAL MODE DECOMPOSITIONS (EEMD); LEARNING EFFECTS; LEAST SQUARES SUPPORT VECTOR MACHINES; SHORT-TERM WIND SPEED FORECASTING; WIND SPEED; WIND SPEED FORECASTING;

FORECASTING;

EID: 84900521858     PISSN: 10006753     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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