{"title":"一种基于聚合度的粒子群算法","authors":"Renxia Wan, Kai Liu","doi":"10.1109/CCET48361.2019.8989389","DOIUrl":null,"url":null,"abstract":"In order to improve the global searching ability of PSO, the weighted aggregation based on a redefined similarity is reconstructed to describe the degree of diversity of the population. The improved PSO also adjusts the particle searching space with an adaptive decision. The experimental analysis shows the effectiveness of the algorithm in terms of optimization ability, convergence speed and stability.","PeriodicalId":231425,"journal":{"name":"2019 IEEE 2nd International Conference on Computer and Communication Engineering Technology (CCET)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Aggregation Degree Based PSO Algorithm\",\"authors\":\"Renxia Wan, Kai Liu\",\"doi\":\"10.1109/CCET48361.2019.8989389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the global searching ability of PSO, the weighted aggregation based on a redefined similarity is reconstructed to describe the degree of diversity of the population. The improved PSO also adjusts the particle searching space with an adaptive decision. The experimental analysis shows the effectiveness of the algorithm in terms of optimization ability, convergence speed and stability.\",\"PeriodicalId\":231425,\"journal\":{\"name\":\"2019 IEEE 2nd International Conference on Computer and Communication Engineering Technology (CCET)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 2nd International Conference on Computer and Communication Engineering Technology (CCET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCET48361.2019.8989389\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 2nd International Conference on Computer and Communication Engineering Technology (CCET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCET48361.2019.8989389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In order to improve the global searching ability of PSO, the weighted aggregation based on a redefined similarity is reconstructed to describe the degree of diversity of the population. The improved PSO also adjusts the particle searching space with an adaptive decision. The experimental analysis shows the effectiveness of the algorithm in terms of optimization ability, convergence speed and stability.
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