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Chaotic Lévy and adaptive restart enhance the Manta Ray foraging optimizer for gene feature selection

Abstract Swarm-based optimization algorithms often face challenges in maintaining an effective exploration–exploitation balance in high-dimensional search spaces. Manta Ray Foraging Optimization (MRFO), while competitive, is hindered by static parameter settings and premature convergence. This study...

Whakaahuatanga katoa

I tiakina i:
Ngā kaituhi matua: Shamsuddeen Adamu, Hitham Alhussian, Said Jadid Abdulkadir, Ayed Alwadain, Sallam O. F. Khairy, Hussaini Mamman, Ismail Said Almuniri, Al Waleed Sulaiman Al Abri, Zaid Fawaz Jarallah, Hamood Saif Hamood Al Fahdi, Maged Nasser, Bander Ali Saleh Al-Rimy
Hōputu: Artigo
Reo:Inglês
I whakaputaina: Nature Portfolio 2025-11-01
Rangatū:Scientific Reports
Ngā marau:
Metaheuristic optimization
Manta Ray foraging optimization
Feature selection
Lévy flight and chaotic maps
Gene expression classification
Multi-objective optimization
Urunga tuihono:https://doi.org/10.1038/s41598-025-25766-y
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