Wind Power Forecasting Using Neural Network Ensembles With Feature Selection
In this paper, a novel ensemble method consisting of neural networks, wavelet transform, feature selection, and partial least-squares regression (PLSR) is proposed for the generation forecasting of a wind farm. Based on the conditional mutual information, a feature selection technique is developed t...
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Main Authors: | , , |
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格式: | Article |
語言: | English |
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2016
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在線閱讀: | https://hdl.handle.net/10356/80608 http://hdl.handle.net/10220/40549 |
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