{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-tutorial-on-particle-swarm-optimization","title":"A tutorial on Particle Swarm Optimization Clustering","arxiv_id":"1809.01942","date":"2018-09-06","proceeding":null,"authors":["Augusto Luis Ballardini"],"abstract":"This paper proposes a tutorial on the Data Clustering technique using the\nParticle Swarm Optimization approach. Following the work proposed by Merwe et\nal. here we present an in-deep analysis of the algorithm together with a Matlab\nimplementation and a short tutorial that explains how to modify the proposed\nimplementation and the effect of the parameters of the original algorithm.\nMoreover, we provide a comparison against the results obtained using the well\nknown K-Means approach. All the source code presented in this paper is publicly\navailable under the GPL-v2 license.","url_abs":"http://arxiv.org/abs/1809.01942v1","url_pdf":"http://arxiv.org/pdf/1809.01942v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-tutorial-on-particle-swarm-optimization","repo_url":"https://github.com/iralabdisco/pso-clustering","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}