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

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...

Descripción completa

Guardado en:
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
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Ejemplares similares