Salp Navigation and Competitive based Parrot Optimizer (SNCPO) for efficient extreme learning machine training and global numerical optimization

Salp Navigation and Competitive based Parrot Optimizer (SNCPO) for efficient extreme learning machine training and global numerical optimization

Abstract Metaheuristic optimization algorithms play a crucial role in solving complex real-world problems, including machine learning parameter tuning, yet many existing approaches struggle with maintaining an effective balance between exploration and exploitation, leading to premature convergence a...

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Bibliographic Details
Main Authors: Oluwatayomi Rereloluwa Adegboye, Afi Kekeli Feda, Ghanshyam G. Tejani, Aseel Smerat, Pankaj Kumar, Ephraim Bonah Agyekum
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Parrot optimizer (PO)
Competitive swarm optimization (CSO)
Salp swarm algorithm (SSA)
Extreme learning machine (ELM)
Online Access:https://doi.org/10.1038/s41598-025-97661-5
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https://doi.org/10.1038/s41598-025-97661-5

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