Feature selection convergence time comparison of various binary metaheuristic algorithms.

Feature selection convergence time comparison of various binary metaheuristic algorithms.

<p>Feature selection convergence time comparison of various binary metaheuristic algorithms.</p>

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Bibliographic Details
Main Author:	Amal H. Alharbi (21755906) (author)
Other Authors:	Faris H. Rizk (21755909) (author), Khaled Sh. Gaber (21755912) (author), Marwa M. Eid (11251630) (author), El-Sayed M. El-kenawy (14581088) (author), Ehsan Khodadadi (21755915) (author), Nima Khodadadi (14581091) (author)
Published:	2025
Subjects:	Medicine Ecology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified sustainable crop production polar rose search optimized model achieved limited agricultural environments inspired algorithm modeled framework &# 8217 ensure optimal growth effectively balancing exploration crops like potatoes computationally efficient predictions bird foraging behavior unified optimization process dipper throated optimization optimization phases metaheuristic optimization wilcoxon tests thereby contributing study presents smart agriculture results demonstrate rbfn ), quality irrigation provide accurate performance improvements including anova hybrid strategy handle complex feature selection extensive experiments dto ), dimensional datasets classification accuracy
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