{"title":"Fuzzy Parameter Particle Swarm Optimization","authors":"P. Yadmellat, S. Salehizadeh, M. Menhaj","doi":"10.1109/ICINIS.2008.111","DOIUrl":null,"url":null,"abstract":"This paper proposes a new fuzzy tuned parameter particle swarm optimization (FPPSO) which remarkably outperforms the standard PSO as well as the previous fuzzy based approaches. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with that of the other algorithms known as fuzzy based PSO. Numerical results indicate that FPPSO is considerably competitive due to its ability to find the functions' global optimum as well as its better convergence performance..","PeriodicalId":185739,"journal":{"name":"2008 First International Conference on Intelligent Networks and Intelligent Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2008.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This paper proposes a new fuzzy tuned parameter particle swarm optimization (FPPSO) which remarkably outperforms the standard PSO as well as the previous fuzzy based approaches. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with that of the other algorithms known as fuzzy based PSO. Numerical results indicate that FPPSO is considerably competitive due to its ability to find the functions' global optimum as well as its better convergence performance..
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