Interpretable wind speed prediction with multivariate time series and temporal fusion transformers

Wind power has been utilized well in power systems, so steady and successful wind speed forecasting is crucial to security management power grid market economy. To date, most researchers have often discounted the interpretability of prediction models, leading to obscure forecasts. This study puts fo...

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Vydáno v:	Energy (Oxford) Ročník 252; s. 123990
Hlavní autoři:	Wu, Binrong, Wang, Lin, Zeng, Yu-Rong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.08.2022 Elsevier BV
Témata:	Algorithms Canada Decomposition Deep learning Economic forecasting Empirical analysis energy Evolutionary computation Forecasting Interpretable forecasting Machine learning Market economies market economy Mathematical models Meteorological data Multisource data Optimization Performance measurement prediction Prediction models Security management Sequences temporal variation time series analysis Variational mode decomposition Wind power Wind speed Wind speed forecasting Canada Deep learning Variational mode decomposition Interpretable forecasting Wind speed forecasting Multisource data
ISSN:	0360-5442, 1873-6785
On-line přístup:	Získat plný text
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