{"title":"粒子群优化:一种综合的理论方法","authors":"Chao-Wei Chou, Hsin-Hui Lin, Jiann-Horng Lin","doi":"10.1109/ICCCYB.2006.305693","DOIUrl":null,"url":null,"abstract":"In this paper, a general and integrated form is proposed for the different kinds of particle swarm optimization. Also, some related theoretical results are given, including a convergence theorem for the random selection case and a lemma on probability percentile. To compare different PSO algorithms in effectiveness and efficiency, we propose three comparison indexes of universal standard.","PeriodicalId":160588,"journal":{"name":"2006 IEEE International Conference on Computational Cybernetics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Note on Particle Swarm Optimization: An integrated and theoretical approach\",\"authors\":\"Chao-Wei Chou, Hsin-Hui Lin, Jiann-Horng Lin\",\"doi\":\"10.1109/ICCCYB.2006.305693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a general and integrated form is proposed for the different kinds of particle swarm optimization. Also, some related theoretical results are given, including a convergence theorem for the random selection case and a lemma on probability percentile. To compare different PSO algorithms in effectiveness and efficiency, we propose three comparison indexes of universal standard.\",\"PeriodicalId\":160588,\"journal\":{\"name\":\"2006 IEEE International Conference on Computational Cybernetics\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Conference on Computational Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCYB.2006.305693\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Conference on Computational Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCYB.2006.305693","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Note on Particle Swarm Optimization: An integrated and theoretical approach
In this paper, a general and integrated form is proposed for the different kinds of particle swarm optimization. Also, some related theoretical results are given, including a convergence theorem for the random selection case and a lemma on probability percentile. To compare different PSO algorithms in effectiveness and efficiency, we propose three comparison indexes of universal standard.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
