A new intelligent method based on combination of VMD and ELM for short term wind power forecasting

Neurocomputing

Volumn 203, Issue , 2016, Pages 111-120

  Abdoos, Ali Akbar ^a  

^a BABOL NOSHIRVANI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Extreme Learning Machine (ELM); Pattern recognition; Variational Mode Decomposition (VMD); Wind power

Indexed keywords

ELECTRIC POWER SYSTEM INTERCONNECTION; ELECTRIC UTILITIES; ENERGY RESOURCES; FEATURE EXTRACTION; FORECASTING; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; PATTERN RECOGNITION; TIME SERIES; WIND; WIND EFFECTS; WIND POWER;

COMPUTATIONAL TIME; EXTREME LEARNING MACHINE; FEATURE SELECTION METHODS; GRAM-SCHMIDT ORTHOGONALIZATIONS; INTELLIGENT METHOD; MODE DECOMPOSITION; SHORT-TERM WIND POWER FORECASTING; WIND POWER FORECASTING;

WEATHER FORECASTING;

ACCURACY; ARTICLE; CONTROLLED STUDY; EXTREME LEARNING MACHINE; FORECASTING; INTERMETHOD COMPARISON; MACHINE LEARNING; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; PRIORITY JOURNAL; SPAIN; UNITED STATES; VARIATIONAL MODE DECOMPOSITION; WIND POWER;

EID: 84971472399     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2016.03.054     Document Type: Article

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