System flow of CO-RF model for SR prediction.

<div><p>In the contemporary context of a burgeoning energy crisis, the accurate and dependable prediction of Solar Radiation (SR) has emerged as an indispensable component within thermal systems to facilitate renewable energy generation. Machine Learning (ML) models have gained widesprea...

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محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ibrahim Al-Shourbaji (20460541) (author)
مؤلفون آخرون:	Pramod H. Kachare (20460544) (author), Abdoh Jabbari (17541360) (author), Raimund Kirner (20460547) (author), Digambar Puri (20460550) (author), Mostafa Mehanawi (20460553) (author), Abdalla Alameen (20460556) (author)
منشور في:	2024
الموضوعات:	Biotechnology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified quantitative analysis demonstrates gained widespread recognition burgeoning energy crisis standalone random forest hourly sr forecasting co component plays 2 </ sup div >< p rf model surpasses random forest >< sup r </ testing phases subsequently serving sr prediction solar radiation second dataset rf model rf ), proposed co pivotal role paper introduces machine learning logistic regression informative features improving prediction first dataset developed co determination (< dependable prediction contemporary context computational efficiency cheetah optimizer
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System flow of CO-RF model for SR prediction.

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