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Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search
Joint Authors
Chen, Xuejun
Jin, Shiqiang
Qin, Shanshan
Li, Laping
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-07-15
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
The support vector regression (SVR) and neural network (NN) are both new tools from the artificial intelligence field, which have been successfully exploited to solve various problems especially for time series forecasting.
However, traditional SVR and NN cannot accurately describe intricate time series with the characteristics of high volatility, nonstationarity, and nonlinearity, such as wind speed and electricity price time series.
This study proposes an ensemble approach on the basis of 5-3 Hanning filter (5-3H) and wavelet denoising (WD) techniques, in conjunction with artificial intelligence optimization based SVR and NN model.
So as to confirm the validity of the proposed model, two applicative case studies are conducted in terms of wind speed series from Gansu Province in China and electricity price from New South Wales in Australia.
The computational results reveal that cuckoo search (CS) outperforms both PSO and GA with respect to convergence and global searching capacity, and the proposed CS-based hybrid model is effective and feasible in generating more reliable and skillful forecasts.
American Psychological Association (APA)
Chen, Xuejun& Jin, Shiqiang& Qin, Shanshan& Li, Laping. 2015. Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-18.
https://search.emarefa.net/detail/BIM-1074266
Modern Language Association (MLA)
Chen, Xuejun…[et al.]. Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search. Mathematical Problems in Engineering No. 2015 (2015), pp.1-18.
https://search.emarefa.net/detail/BIM-1074266
American Medical Association (AMA)
Chen, Xuejun& Jin, Shiqiang& Qin, Shanshan& Li, Laping. Short-Term Wind Speed Forecasting Study and Its Application Using a Hybrid Model Optimized by Cuckoo Search. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-18.
https://search.emarefa.net/detail/BIM-1074266
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074266