Predictive analysis of porous media–cooled photovoltaic panels using gradient-boosting machine learning models

This study develops a robust machine learning framework to predict the temperature and power output of PV panels cooled with porous media. Four advanced gradient-boosting algorithms, CatBoost, XGBoost, LightGBM, and GBM, were evaluated using five progressively complex models that incorporate key coo...

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Bibliographic Details

Main Authors:	Masalha, Ismail, Alahmer, Ali, Alsabagh, Abdel Salam, Badran, Omar, Masuri, Siti Ujila
Format:	Article
Language:	en
Published:	Elsevier 2026
Subjects:	Renewable Energy, Sustainability and the Environment Engineering (all)
Online Access:	http://psasir.upm.edu.my/id/eprint/122535/1/122535.pdf http://psasir.upm.edu.my/id/eprint/122535/ https://linkinghub.elsevier.com/retrieve/pii/S0960148125027855
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