PMSOMA: optical microscope algorithm based on piecewise linear chaotic mapping and sparse adaptive exploration

Bibliographic Details
Title: PMSOMA: optical microscope algorithm based on piecewise linear chaotic mapping and sparse adaptive exploration
Authors: Linyi Guo, Wei Gu
Source: Scientific Reports, Vol 14, Iss 1, Pp 1-27 (2024)
Publisher Information: Nature Portfolio, 2024.
Publication Year: 2024
Collection: LCC:Medicine
LCC:Science
Subject Terms: Optical microscope algorithm, Piecewise linear chaotic mapping, Sparse adaptive exploration mechanism, Engineering problem, Medicine, Science
More Details: Abstract The optical microscope algorithm (OMA) is a metaheuristic algorithm that draws inspiration from the magnifying functionality of optical microscopes. This study introduces an enhanced variant of OMA, termed PMSOMA, designed to mitigate the original version's limitations, notably its slow convergence rates and vulnerability to local optima. PMSOMA integrates a piecewise linear chaotic map to refine population initialization and augment diversity, alongside a sparse adaptive exploration mechanism to bolster search efficacy. The performance of PMSOMA was rigorously tested using a suite of 50 benchmark functions, the CEC2017 test suite, feature selection datasets, and three classical engineering challenges. The empirical findings confirm that PMSOMA surpasses both the original OMA and competing algorithms by delivering superior solutions, accelerating convergence, and demonstrating enhanced robustness in convergence.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-024-71828-y
Access URL: https://doaj.org/article/e4cbb7fe91874e6a84c11901eb06a455
Accession Number: edsdoj.4cbb7fe91874e6a84c11901eb06a455
Database: Directory of Open Access Journals
Full text is not displayed to guests.
More Details
ISSN:20452322
DOI:10.1038/s41598-024-71828-y
Published in:Scientific Reports
Language:English