A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets

•Improve the accuracy and speed of the short term wind speed forecasting by a hybrid forecasting model.•Propose a feature selection method based on entropy and mutual information technique.•Implement a deep learning time series prediction model based on LSTM.•Using the Wavelet Transform module elimi...

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Veröffentlicht in:	Energy conversion and management Jg. 213; S. 112824
Hauptverfasser:	Memarzadeh, Gholamreza, Keynia, Farshid
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.06.2020 Elsevier Science Ltd
Schlagworte:	accuracy administrative management algorithms artificial intelligence behavior Clean energy Crow search algorithm Deep learning Electric power generation Electric power grids energy conversion Energy sources Entropy Feature selection Forecasting information Iran Long short term memory Machine learning Middle East Neural network Neural networks power generation prediction Search algorithms Spain time series analysis wavelet Wavelet transform Wavelet transforms Wind power Wind power generation Wind speed Wind speed forecasting Middle East Iran Spain Feature selection Crow search algorithm Wavelet transform Neural network Long short term memory Wind speed forecasting
ISSN:	0196-8904, 1879-2227
Online-Zugang:	Volltext
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