Short-Term Wind Speed Prediction Using EEMD-LSSVM Model
Joint Authors
Yuan, Xiaohui
Kang, Aiqing
Tan, Qingxiong
Lei, Xiaohui
Yuan, Yanbin
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-22, 22 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-12
Country of Publication
Egypt
No. of Pages
22
Main Subjects
Abstract EN
Hybrid Ensemble Empirical Mode Decomposition (EEMD) and Least Square Support Vector Machine (LSSVM) is proposed to improve short-term wind speed forecasting precision.
The EEMD is firstly utilized to decompose the original wind speed time series into a set of subseries.
Then the LSSVM models are established to forecast these subseries.
Partial autocorrelation function is adopted to analyze the inner relationships between the historical wind speed series in order to determine input variables of LSSVM models for prediction of every subseries.
Finally, the superposition principle is employed to sum the predicted values of every subseries as the final wind speed prediction.
The performance of hybrid model is evaluated based on six metrics.
Compared with LSSVM, Back Propagation Neural Networks (BP), Auto-Regressive Integrated Moving Average (ARIMA), combination of Empirical Mode Decomposition (EMD) with LSSVM, and hybrid EEMD with ARIMA models, the wind speed forecasting results show that the proposed hybrid model outperforms these models in terms of six metrics.
Furthermore, the scatter diagrams of predicted versus actual wind speed and histograms of prediction errors are presented to verify the superiority of the hybrid model in short-term wind speed prediction.
American Psychological Association (APA)
Kang, Aiqing& Tan, Qingxiong& Yuan, Xiaohui& Lei, Xiaohui& Yuan, Yanbin. 2017. Short-Term Wind Speed Prediction Using EEMD-LSSVM Model. Advances in Meteorology،Vol. 2017, no. 2017, pp.1-22.
https://search.emarefa.net/detail/BIM-1122856
Modern Language Association (MLA)
Kang, Aiqing…[et al.]. Short-Term Wind Speed Prediction Using EEMD-LSSVM Model. Advances in Meteorology No. 2017 (2017), pp.1-22.
https://search.emarefa.net/detail/BIM-1122856
American Medical Association (AMA)
Kang, Aiqing& Tan, Qingxiong& Yuan, Xiaohui& Lei, Xiaohui& Yuan, Yanbin. Short-Term Wind Speed Prediction Using EEMD-LSSVM Model. Advances in Meteorology. 2017. Vol. 2017, no. 2017, pp.1-22.
https://search.emarefa.net/detail/BIM-1122856
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1122856