{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:47:35Z","timestamp":1783579655449,"version":"3.55.0"},"reference-count":77,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T00:00:00Z","timestamp":1614902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010052","name":"Northumbria University","doi-asserted-by":"publisher","award":["RDF PhD Studentship"],"award-info":[{"award-number":["RDF PhD Studentship"]}],"id":[{"id":"10.13039\/100010052","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this research, we propose two Particle Swarm Optimisation (PSO) variants to undertake feature selection tasks. The aim is to overcome two major shortcomings of the original PSO model, i.e., premature convergence and weak exploitation around the near optimal solutions. The first proposed PSO variant incorporates four key operations, including a modified PSO operation with rectified personal and global best signals, spiral search based local exploitation, Gaussian distribution-based swarm leader enhancement, and mirroring and mutation operations for worst solution improvement. The second proposed PSO model enhances the first one through four new strategies, i.e., an adaptive exemplar breeding mechanism incorporating multiple optimal signals, nonlinear function oriented search coefficients, exponential and scattering schemes for swarm leader, and worst solution enhancement, respectively. In comparison with a set of 15 classical and advanced search methods, the proposed models illustrate statistical superiority for discriminative feature selection for a total of 13 data sets.<\/jats:p>","DOI":"10.3390\/s21051816","type":"journal-article","created":{"date-parts":[[2021,3,5]],"date-time":"2021-03-05T11:46:09Z","timestamp":1614944769000},"page":"1816","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["Feature Selection Using Enhanced Particle Swarm Optimisation for Classification Models"],"prefix":"10.3390","volume":"21","author":[{"given":"Hailun","family":"Xie","sequence":"first","affiliation":[{"name":"Computational Intelligence Research Group, Department of Computer and Information Sciences, Faculty of Engineering and Environment, University of Northumbria, Newcastle upon Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zhang","sequence":"additional","affiliation":[{"name":"Computational Intelligence Research Group, Department of Computer and Information Sciences, Faculty of Engineering and Environment, University of Northumbria, Newcastle upon Tyne NE1 8ST, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chee Peng","family":"Lim","sequence":"additional","affiliation":[{"name":"Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC 3216, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2587-8090","authenticated-orcid":false,"given":"Yonghong","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Tongda, Nanjing University of Posts and Telecommunications, Nanjing 210049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.patcog.2009.06.009","article-title":"Feature subset selection in large dimensionality domains","volume":"43","author":"Gheyas","year":"2010","journal-title":"Pattern Recognit."},{"key":"ref_2","unstructured":"Mirjalili, S., Dong, J.S., and Lewis, A. 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