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A Compound Structure for Wind Speed Forecasting Using MKLSSVM with Feature Selection and Parameter Optimization
Joint Authors
Xiong, Nan
Sun, Sizhou
Fu, Jingqi
Zhu, Feng
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-14
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
The aims of this study contribute to a new hybrid model by combining ensemble empirical mode decomposition (EEMD) with multikernel function least square support vector machine (MKLSSVM) optimized by hybrid gravitation search algorithm (HGSA) for short-term wind speed prediction.
In the forecasting process, EEMD is adopted to make the original wind speed data decomposed into intrinsic mode functions (IMFs) and one residual firstly.
Then, partial autocorrelation function (PACF) is applied to identify the correlation between the corresponding decomposed components.
Subsequently, the MKLSSVM using multikernel function of radial basis function (RBF) and polynomial (Poly) kernel function by weight coefficient is exploited as core forecasting engine to make the short-term wind speed prediction.
To improve the regression performance, the binary-value GSA (BGSA) in HGSA is utilized as feature selection approach to remove the ineffective candidates and reconstruct the most relevant feature input-matrix for the forecasting engine, while real-value GSA (RGSA) makes the parameter combination optimization of MKLSSVM model.
In the end, these respective decomposed subseries forecasting results are combined into the final forecasting values by aggregate calculation.
Numerical results and comparable analysis illustrate the excellent performance of the EEMD-HGSA-MKLSSVM model when applied in the short-term wind speed forecasting.
American Psychological Association (APA)
Sun, Sizhou& Fu, Jingqi& Zhu, Feng& Xiong, Nan. 2018. A Compound Structure for Wind Speed Forecasting Using MKLSSVM with Feature Selection and Parameter Optimization. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-21.
https://search.emarefa.net/detail/BIM-1209601
Modern Language Association (MLA)
Sun, Sizhou…[et al.]. A Compound Structure for Wind Speed Forecasting Using MKLSSVM with Feature Selection and Parameter Optimization. Mathematical Problems in Engineering No. 2018 (2018), pp.1-21.
https://search.emarefa.net/detail/BIM-1209601
American Medical Association (AMA)
Sun, Sizhou& Fu, Jingqi& Zhu, Feng& Xiong, Nan. A Compound Structure for Wind Speed Forecasting Using MKLSSVM with Feature Selection and Parameter Optimization. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-21.
https://search.emarefa.net/detail/BIM-1209601
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209601