Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling

标题
Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling
作者
关键词
Deep learning, Electricity price forecasting (EPF), Electricity market coupling, Feature selection, Long short-term memory (LSTM), The Nord Pool system price
出版物
ENERGY
Volume 237, Issue -, Pages 121543
出版商
Elsevier BV
发表日期
2021-07-27
DOI
10.1016/j.energy.2021.121543

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started