The hybrid model of empirical wavelet transform and relevance vector regression for monthly wind speed prediction |
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Authors: | Sheng-Wei Fei |
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Institution: | 1. College of Mechanical Engineering, Donghua University , Shanghai, China feipd@163.com |
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Abstract: | ABSTRACT In order to improve the prediction ability for the monthly wind speed of RVR, the hybrid model of empirical wavelet transform and relevance vector regression (EWT-RVR) is proposed for monthly wind speed prediction in this study. Compared with empirical mode decomposition (EMD), empirical wavelet transform (EWT) can obtain a more consistent decomposition and have a mathematical theory. In order to testify the superiority of EWT-RVR, several traditional RVR models are used to compare with the proposed EWT-RVR method under the situation of the same embedding dimensions. The experimental results show that the proposed EWT-RVR method has a better prediction ability for monthly wind speed than RVR. It can be concluded that the proposed EWT-RVR method for monthly wind speed is effective. |
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Keywords: | Empirical wavelet decomposed signals empirical wavelet transform prediction relevance vector regression wind speed |
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