Optimized deep neural network architectures for energy consumption and PV production forecasting
- DOI
- 10.1016/j.esr.2025.101704
- Published
- 2025-05
- Container
- Energy Strategy Reviews
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.esr.2025.101704,
title = {Optimized deep neural network architectures for energy consumption and PV production forecasting},
author = {Eghbal Hosseini and Barzan Saeedpour and Mohsen Banaei and Razgar Ebrahimy},
year = {2025},
journal = {Energy Strategy Reviews},
doi = {10.1016/j.esr.2025.101704},
url = {https://doi.org/10.1016/j.esr.2025.101704}
}RIS
TY - JOUR TI - Optimized deep neural network architectures for energy consumption and PV production forecasting AU - Eghbal Hosseini AU - Barzan Saeedpour AU - Mohsen Banaei AU - Razgar Ebrahimy PY - 2025 JO - Energy Strategy Reviews DO - 10.1016/j.esr.2025.101704 UR - https://doi.org/10.1016/j.esr.2025.101704 ER -
APA
Hosseini, E., Saeedpour, B., Banaei, M., & Ebrahimy, R. (2025). Optimized deep neural network architectures for energy consumption and PV production forecasting. Energy Strategy Reviews. https://doi.org/10.1016/j.esr.2025.101704
Source records
- crossref · retrieved 2026-11-10T13:06:20.869Z