A Novel Empirical Mode Decomposition with Support Vector Regression for Wind Speed Forecasting

IEEE Transactions on Neural Networks and Learning Systems

Volumn 27, Issue 8, 2016, Pages 1793-1798

  Ren, Ye ^a   Suganthan, Ponnuthurai Nagaratnam ^a   Srikanth, Narasimalu ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Empirical mode decomposition (EMD); support vector regression (SVR); wind energy; wind speed forecasting

Indexed keywords

COMPUTATIONAL COMPLEXITY; FORECASTING; SCHEDULING; SIGNAL PROCESSING; SPEED; WIND POWER;

EMPIRICAL MODE DECOMPOSITION; INTRINSIC MODE FUNCTIONS; MAINTENANCE SCHEDULING; RENEWABLE ENERGY SOURCE; SUPPORT VECTOR REGRESSION (SVR); WIND SPEED DATA; WIND SPEED FORECASTING; WIND SPEED TIME SERIES;

WIND;

EID: 84907704597     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2351391     Document Type: Article

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