Optimizing Nanofluid Hybrid Solar Collectors through Artificial Intelligence Models
Safae Margoum,
Bekkay Hajji,
Stefano Aneli
et al.
Abstract:This study systematically explores and compares the performance of various artificial-intelligence (AI)-based models to predict the electrical and thermal efficiency of photovoltaic–thermal systems (PVTs) cooled by nanofluids. Employing extreme gradient boosting (XGB), extra tree regression (ETR), and k-nearest-neighbor (KNN) regression models, their accuracy is quantitatively evaluated, and their effectiveness measured. The results demonstrate that both XGB and ETR models consistently outperform KNN in accura… Show more
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