Global solar energy potential forecasting through machine learning and deep learning models
- DOI
- 10.1038/s41598-026-41357-x
- Published
- 2026-02-25
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-41357-x,
title = {Global solar energy potential forecasting through machine learning and deep learning models},
author = {Muhammad Amir Raza and Abdul Karim and Muneera Altayeb and Muhammad I. Masud and Muhammad Faheem and Touqeer Ahmed Jumani and Mohammed Aman},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-41357-x},
url = {https://doi.org/10.1038/s41598-026-41357-x}
}RIS
TY - JOUR TI - Global solar energy potential forecasting through machine learning and deep learning models AU - Muhammad Amir Raza AU - Abdul Karim AU - Muneera Altayeb AU - Muhammad I. Masud AU - Muhammad Faheem AU - Touqeer Ahmed Jumani AU - Mohammed Aman PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-41357-x UR - https://doi.org/10.1038/s41598-026-41357-x ER -
APA
Raza, M. A., Karim, A., Altayeb, M., Masud, M. I., Faheem, M., Jumani, T. A., & Aman, M. (2026). Global solar energy potential forecasting through machine learning and deep learning models. Scientific Reports. https://doi.org/10.1038/s41598-026-41357-x
Source records
- crossref · retrieved 2026-09-27T08:13:44.959Z