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Abstract and Applied Analysis
Volume 2014, Article ID 693205, 14 pages
http://dx.doi.org/10.1155/2014/693205
Research Article

Hybrid Wind Speed Forecasting Model Study Based on SSA and Intelligent Optimized Algorithm

Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, Lanzhou 730000, China

Received 9 January 2014; Accepted 13 February 2014; Published 3 April 2014

Academic Editor: Suohai Fan

Copyright © 2014 Wenyu Zhang 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 [8 citations]

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

  • As’ad Zakaria, Wolf – Gerrit – Früh, and Firas Basim Ismail, “Wind resource forecasting using enhanced measure correlate predict (MCP),” vol. 2035, pp. 040005, . View at Publisher · View at Google Scholar
  • Yanqiu Sun, “A Hybrid Approach by Integrating Brain Storm Optimization Algorithm with Grey Neural Network for Stock Index Forecasting,” Abstract and Applied Analysis, vol. 2014, pp. 1–10, 2014. View at Publisher · View at Google Scholar
  • Jianzhou Wang, Qingping Zhou, Haiyan Jiang, and Ru Hou, “Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm,” Mathematical Problems in Engineering, vol. 2015, pp. 1–13, 2015. View at Publisher · View at Google Scholar
  • Lida Barba, and Nibaldo Rodríguez, “Hybrid Models Based on Singular Values and Autoregressive Methods for Multistep Ahead Forecasting of Traffic Accidents,” Mathematical Problems in Engineering, vol. 2016, pp. 1–14, 2016. View at Publisher · View at Google Scholar
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  • Nabiha Brahmi, Sana Charfi, and Maher Chaabene, “Wind potential assessment for an efficient wind farm sizing,” Wind Engineering, pp. 0309524X1772199, 2017. View at Publisher · View at Google Scholar
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  • Ye Zhang, Shiping Yang, Zhenhai Guo, Yanling Guo, and Jing Zhao, “Wind speed forecasting based on wavelet decomposition and wavelet neural networks optimized by the Cuckoo search algorithm,” Atmospheric and Oceanic Science Letters, pp. 1–9, 2019. View at Publisher · View at Google Scholar