Probability Density Forecasting of Wind Speed Based on Quantile Regression and Kernel Density Estimation

Based on quantile regression (QR) and kernel density estimation (KDE), a framework for probability density forecasting of short-term wind speed is proposed in this study. The empirical mode decomposition (EMD) technique is implemented to reduce the noise of raw wind speed series. Both linear QR (LQR...

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Autors principals:	Lei Zhang, Lun Xie, Qinkai Han, Zhiliang Wang, Chen Huang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2020-11-01
Col·lecció:	Energies
Matèries:	probability density forecasting wind speed series quantile regression kernel density estimation signal decomposing algorithm
Accés en línia:	https://www.mdpi.com/1996-1073/13/22/6125
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