Stacking Ensemble Methodology Using Deep Learning and ARIMA Models for Short-Term Load Forecasting

Short-Term Load Forecasting is critical for reliable power system operation, and the search for enhanced methodologies has been a constant field of investigation, particularly in an increasingly competitive environment where the market operator and its participants need to better inform their decisi...

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Detalles Bibliográficos
Autores principales:	Pedro M. R. Bento, Jose A. N. Pombo, Maria R. A. Calado, Silvio J. P. S. Mariano
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ARIMA models correlation analysis deep learning deep neural networks ensemble methods ISO New England Technology T
Acceso en línea:	https://doaj.org/article/dd27aaef327f4061b5d5426f0f4a3a92
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Stacking Ensemble Methodology Using Deep Learning and ARIMA Models for Short-Term Load Forecasting

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