{"title":"基于混沌理论的种群迁移新算法","authors":"Yuwu Lu, Xueying Liu","doi":"10.1109/IPTC.2011.44","DOIUrl":null,"url":null,"abstract":"In order to improve the solution accuracy and the convergence of Population Migration Algorithm (PMA) and avoiding its prematurity, in this paper, we combined chaos theory with PMA. By introducing logistic mapping of chaos theory into PMA, we use the ergodicity, randomicity and regularity of chaos theory to attain an improved algorithm. The experimental results show that: by introducing the ergodicity, randomicity and regularity of chaos theory into PMA, the solution accuracy and the convergence property of PMA can effectively improve and effectively avoid prematurity phenomenon. The improved algorithm performs very well.","PeriodicalId":388589,"journal":{"name":"2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A New Population Migration Algorithm Based on the Chaos Theory\",\"authors\":\"Yuwu Lu, Xueying Liu\",\"doi\":\"10.1109/IPTC.2011.44\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the solution accuracy and the convergence of Population Migration Algorithm (PMA) and avoiding its prematurity, in this paper, we combined chaos theory with PMA. By introducing logistic mapping of chaos theory into PMA, we use the ergodicity, randomicity and regularity of chaos theory to attain an improved algorithm. The experimental results show that: by introducing the ergodicity, randomicity and regularity of chaos theory into PMA, the solution accuracy and the convergence property of PMA can effectively improve and effectively avoid prematurity phenomenon. The improved algorithm performs very well.\",\"PeriodicalId\":388589,\"journal\":{\"name\":\"2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTC.2011.44\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 2nd International Symposium on Intelligence Information Processing and Trusted Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTC.2011.44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Population Migration Algorithm Based on the Chaos Theory
In order to improve the solution accuracy and the convergence of Population Migration Algorithm (PMA) and avoiding its prematurity, in this paper, we combined chaos theory with PMA. By introducing logistic mapping of chaos theory into PMA, we use the ergodicity, randomicity and regularity of chaos theory to attain an improved algorithm. The experimental results show that: by introducing the ergodicity, randomicity and regularity of chaos theory into PMA, the solution accuracy and the convergence property of PMA can effectively improve and effectively avoid prematurity phenomenon. The improved algorithm performs very well.