{"title":"粒子群优化的应用技术","authors":"Z. Meng","doi":"10.1109/BWCCA.2010.138","DOIUrl":null,"url":null,"abstract":"Particle swarm optimizer (PSO) is a powerful tool for designing antennas, solving inverse scattering problems, and so on. The algorithm is controlled with several parameters. Unless the parameters are selected appropriately, the search efficiency of PSO drops significantly. There are, however, no clear rules for the selection, and users have considerable difficulty to use PSO efficiently. This paper proposes a guideline for the selection to make the algorithm easy-to-use and keeping high performance.","PeriodicalId":196401,"journal":{"name":"2010 International Conference on Broadband, Wireless Computing, Communication and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application Techniques of Particle Swarm Optimization\",\"authors\":\"Z. Meng\",\"doi\":\"10.1109/BWCCA.2010.138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Particle swarm optimizer (PSO) is a powerful tool for designing antennas, solving inverse scattering problems, and so on. The algorithm is controlled with several parameters. Unless the parameters are selected appropriately, the search efficiency of PSO drops significantly. There are, however, no clear rules for the selection, and users have considerable difficulty to use PSO efficiently. This paper proposes a guideline for the selection to make the algorithm easy-to-use and keeping high performance.\",\"PeriodicalId\":196401,\"journal\":{\"name\":\"2010 International Conference on Broadband, Wireless Computing, Communication and Applications\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Broadband, Wireless Computing, Communication and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BWCCA.2010.138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Broadband, Wireless Computing, Communication and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BWCCA.2010.138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application Techniques of Particle Swarm Optimization
Particle swarm optimizer (PSO) is a powerful tool for designing antennas, solving inverse scattering problems, and so on. The algorithm is controlled with several parameters. Unless the parameters are selected appropriately, the search efficiency of PSO drops significantly. There are, however, no clear rules for the selection, and users have considerable difficulty to use PSO efficiently. This paper proposes a guideline for the selection to make the algorithm easy-to-use and keeping high performance.