Short-Term Wind Speed Forecast Based on B-Spline Neural Network Optimized by PSO
Joint Authors
Wu, Zhongqiang
Jia, Wenjing
Zhao, Liru
Wu, Changhan
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-28
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Considering the randomness and volatility of wind, a method based on B-spline neural network optimized by particle swarm optimization is proposed to predict the short-term wind speed.
The B-spline neural network can change the division of input space and the definition of basis function flexibly.
For any input, only a few outputs of hidden layers are nonzero, the outputs are simple, and the convergence speed is fast, but it is easy to fall into local minimum.
The traditional method to divide the input space is thoughtless and it will influence the final prediction accuracy.
Particle swarm optimization is adopted to solve the problem by optimizing the nodes.
Simulated results show that it has higher prediction accuracy than traditional B-spline neural network and BP neural network.
American Psychological Association (APA)
Wu, Zhongqiang& Jia, Wenjing& Zhao, Liru& Wu, Changhan. 2015. Short-Term Wind Speed Forecast Based on B-Spline Neural Network Optimized by PSO. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1073393
Modern Language Association (MLA)
Wu, Zhongqiang…[et al.]. Short-Term Wind Speed Forecast Based on B-Spline Neural Network Optimized by PSO. Mathematical Problems in Engineering No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1073393
American Medical Association (AMA)
Wu, Zhongqiang& Jia, Wenjing& Zhao, Liru& Wu, Changhan. Short-Term Wind Speed Forecast Based on B-Spline Neural Network Optimized by PSO. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1073393
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073393