A Hybrid Approach for Short-Term Forecasting of Wind Speed
Joint Authors
Tatinati, Sivanagaraja
Veluvolu, Kalyana C.
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-24
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
We propose a hybrid method for forecasting the wind speed.
The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition.
Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs.
Least squares-support vector machines are employed for IMFs with weak correlation factor, and autoregressive model with Kalman filter is employed for IMFs with high correlation factor.
Multistep prediction with the proposed hybrid method resulted in improved forecasting.
Results with wind speed data show that the proposed method provides better forecasting compared to the existing methods.
American Psychological Association (APA)
Tatinati, Sivanagaraja& Veluvolu, Kalyana C.. 2013. A Hybrid Approach for Short-Term Forecasting of Wind Speed. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-1033054
Modern Language Association (MLA)
Tatinati, Sivanagaraja& Veluvolu, Kalyana C.. A Hybrid Approach for Short-Term Forecasting of Wind Speed. The Scientific World Journal No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-1033054
American Medical Association (AMA)
Tatinati, Sivanagaraja& Veluvolu, Kalyana C.. A Hybrid Approach for Short-Term Forecasting of Wind Speed. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-1033054
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033054