Wind speed prediction by a swarm intelligence based deep learning model via signal decomposition and parameter optimization using improved chimp optimization algorithm

Accurate prediction of wind speed plays a very important role in the stable operation of wind power plants. In this study, the goal is to establish a hybrid wind speed prediction model based on Time Varying Filtering based Empirical Mode Decomposition (TVFEMD), Fuzzy Entropy (FE), Partial Autocorrel...

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Bibliographic Details
Published in:	Energy (Oxford) Vol. 276; p. 127526
Main Authors:	Suo, Leiming, Peng, Tian, Song, Shihao, Zhang, Chu, Wang, Yuhan, Fu, Yongyan, Nazir, Muhammad Shahzad
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.08.2023
Subjects:	algorithms autocorrelation BiGRU Chimp optimization algorithm Deep learning energy entropy prediction swarms TVFEMD wind power wind speed Wind speed prediction Deep learning BiGRU Chimp optimization algorithm Wind speed prediction TVFEMD
ISSN:	0360-5442
Online Access:	Get full text
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