Forecasting Day-Ahead Electricity Metrics with Artificial Neural Networks

As artificial neural network architectures grow increasingly more efficient in time-series prediction tasks, their use for day-ahead electricity price and demand prediction, a task with very specific rules and highly volatile dataset values, grows more attractive. Without a standardized way to compa...

Descripción completa

Detalles Bibliográficos
Autores principales: Pavićević, Milutin, Popović, Tomo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839566/
https://www.ncbi.nlm.nih.gov/pubmed/35161797
http://dx.doi.org/10.3390/s22031051

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839566/
https://www.ncbi.nlm.nih.gov/pubmed/35161797
http://dx.doi.org/10.3390/s22031051

Ejemplares similares