Electric load forecasting based on Long-Short-Term-Memory network via simplex optimizer during COVID-19

Electric load forecasting is a challenging research, which is of great significance to the safe and stable operation of power grid in epidemic period. In this paper, Long-Short-Term-Memory (LSTM) model with simplex optimizer is proposed to forecast the electric load for an enterprise during the COVI...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Xiaole, Wang, Yiqin, Ma, Guibo, Chen, Xin, Shen, Qianxiang, Yang, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2022
Materias:
2021 7th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2021), November 19–21, 2021, Guangzhou, China
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920819/
http://dx.doi.org/10.1016/j.egyr.2022.03.051

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920819/
http://dx.doi.org/10.1016/j.egyr.2022.03.051

Ejemplares similares