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Journal of Applied Mathematics
Volume 2014, Article ID 437592, 6 pages
http://dx.doi.org/10.1155/2014/437592
Research Article

Day-Ahead Wind Speed Forecasting Using Relevance Vector Machine

1Research Center for Renewable Energy Generation Engineering, Ministry of Education, Hohai University, Nanjing 210098, China
2ALSTOM GRID Technology Center Co., Ltd., Shanghai 201114, China
3ALSTOM Grid Inc., Redmond, WA 98052, USA

Received 31 December 2013; Revised 5 May 2014; Accepted 22 May 2014; Published 12 June 2014

Academic Editor: Hongjie Jia

Copyright © 2014 Guoqiang Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Taiyong Li, Min Zhou, Chaoqi Guo, Jiang Wu, Quanyi Tao, Ting He, Min Luo, and Fan Pan, “Forecasting crude oil price using EEMD and RVM with adaptive PSO-based kernels,” Energies, vol. 9, no. 12, 2016. View at Publisher · View at Google Scholar
  • Haixiang Zang, Lei Fan, Mian Guo, Zhinong Wei, Guoqiang Sun, and Li Zhang, “Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model,” Advances in Meteorology, vol. 2016, pp. 1–10, 2016. View at Publisher · View at Google Scholar
  • Zongjie Wang, and Zhizhong Guo, “Quantitative characterization of uncertainty levels of intermittent power sources,” Journal of Renewable and Sustainable Energy, vol. 10, no. 4, pp. 043304, 2018. View at Publisher · View at Google Scholar