Convergence behavior of different optimization algorithms as feature selectors for SR prediction for (a) dataset-1 and (b) dataset-2.

<p>Convergence behavior of different optimization algorithms as feature selectors for SR prediction for (a) dataset-1 and (b) dataset-2.</p>

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Bibliographic Details
Main Author:	Ibrahim Al-Shourbaji (20460541) (author)
Other Authors:	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)
Published:	2024
Subjects:	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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