A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting

Energy Conversion and Management

Volumn 143, Issue , 2017, Pages 360-376

  Zhang, Chu ^a,b   Zhou, Jianzhong ^a,b   Li, Chaoshun ^a,b   Fu, Wenlong ^c   Peng, Tian ^a,b  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b China Hubei Key Laboratory of Digital Manufacturing   (China)

^c CHINA THREE GORGES UNIVERSITY   (China)

Author keywords

Backtracking search algorithm; Extreme learning machine; Feature selection; Parameter optimization; Variational mode decomposition; Wind speed forecasting

Indexed keywords

AUTOCORRELATION; ELECTRIC POWER GENERATION; ELECTRIC UTILITIES; FEATURE EXTRACTION; FORECASTING; KNOWLEDGE ACQUISITION; LEARNING ALGORITHMS; LEARNING SYSTEMS; PARAMETER ESTIMATION; SIGNAL PROCESSING; SPEED; WIND POWER;

BACKTRACKING SEARCH ALGORITHMS; EXTREME LEARNING MACHINE; MODE DECOMPOSITION; PARAMETER OPTIMIZATION; WIND SPEED FORECASTING;

WIND EFFECTS;

EID: 85017562291     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2017.04.007     Document Type: Article

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