Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm
Joint Authors
Zhou, Qingping
Jiang, Haiyan
Hou, Ru
Wang, Jianzhou
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-07-16
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper develops an effectively intelligent model to forecast short-term wind speed series.
A hybrid forecasting technique is proposed based on recurrence plot (RP) and optimized support vector regression (SVR).
Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast.
To understand the wind system, the wind speed series is analyzed using RP.
Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms.
Those optimized algorithms are genetic algorithm (GA), particle swarm optimization algorithm (PSO), and cuckoo optimization algorithm (COA).
Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test.
The experimental results show that (1) analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2) the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3) the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.
American Psychological Association (APA)
Wang, Jianzhou& Zhou, Qingping& Jiang, Haiyan& Hou, Ru. 2015. Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074301
Modern Language Association (MLA)
Wang, Jianzhou…[et al.]. Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1074301
American Medical Association (AMA)
Wang, Jianzhou& Zhou, Qingping& Jiang, Haiyan& Hou, Ru. Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074301
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074301