Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration
- DOI
- 10.3390/en17112687
- Published
- 2024-06-01
- Container
- Energies
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/en17112687,
title = {Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration},
author = {Ziyang Wang and Masahiro Mae and Takeshi Yamane and Masato Ajisaka and Tatsuya Nakata and Ryuji Matsuhashi},
year = {2024},
journal = {Energies},
doi = {10.3390/en17112687},
url = {https://doi.org/10.3390/en17112687}
}RIS
TY - JOUR TI - Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration AU - Ziyang Wang AU - Masahiro Mae AU - Takeshi Yamane AU - Masato Ajisaka AU - Tatsuya Nakata AU - Ryuji Matsuhashi PY - 2024 JO - Energies DO - 10.3390/en17112687 UR - https://doi.org/10.3390/en17112687 ER -
APA
Wang, Z., Mae, M., Yamane, T., Ajisaka, M., Nakata, T., & Matsuhashi, R. (2024). Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration. Energies. https://doi.org/10.3390/en17112687
Source records
- crossref · retrieved 2026-09-25T22:42:35.383Z