Lightweight deep learning for photovoltaic energy prediction: Optimizing decarbonization in winter houses
- DOI
- 10.1016/j.solener.2025.113567
- Published
- 2025-09
- Container
- Solar Energy
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.solener.2025.113567,
title = {Lightweight deep learning for photovoltaic energy prediction: Optimizing decarbonization in winter houses},
author = {Youssef Jouane and Ilyass Abouelaziz and Imad Saddik and Oussama Oussous},
year = {2025},
journal = {Solar Energy},
doi = {10.1016/j.solener.2025.113567},
url = {https://doi.org/10.1016/j.solener.2025.113567}
}RIS
TY - JOUR TI - Lightweight deep learning for photovoltaic energy prediction: Optimizing decarbonization in winter houses AU - Youssef Jouane AU - Ilyass Abouelaziz AU - Imad Saddik AU - Oussama Oussous PY - 2025 JO - Solar Energy DO - 10.1016/j.solener.2025.113567 UR - https://doi.org/10.1016/j.solener.2025.113567 ER -
APA
Jouane, Y., Abouelaziz, I., Saddik, I., & Oussous, O. (2025). Lightweight deep learning for photovoltaic energy prediction: Optimizing decarbonization in winter houses. Solar Energy. https://doi.org/10.1016/j.solener.2025.113567
Source records
- crossref · retrieved 2026-09-25T11:45:53.955Z