{"title":"聚类分析问题与仿生聚类方法","authors":"E. Benderskaya","doi":"10.1109/SCM.2017.7970526","DOIUrl":null,"url":null,"abstract":"The article presents the analysis of the clustering problem formalization and considers possibilities to use the classical methods and bio-inspired methods for solving problems of the cluster analysis. In this paper we do not present full review of the new clustering methods, but identify some trends in the development of cluster analysis and special attention is given to area of bio-inspired methods for clustering. Oscillatory networks can be considered as way that is proposed by nature for solving problems of data mining and especially for cluster analysis. Opportunities are examined for applying the oscillatory networks for general problems of cluster analysis. Have shown general features compared with various traditional methods for cluster analysis.","PeriodicalId":315574,"journal":{"name":"2017 XX IEEE International Conference on Soft Computing and Measurements (SCM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Cluster analysis problems and bio-inspired clustering methods\",\"authors\":\"E. Benderskaya\",\"doi\":\"10.1109/SCM.2017.7970526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents the analysis of the clustering problem formalization and considers possibilities to use the classical methods and bio-inspired methods for solving problems of the cluster analysis. In this paper we do not present full review of the new clustering methods, but identify some trends in the development of cluster analysis and special attention is given to area of bio-inspired methods for clustering. Oscillatory networks can be considered as way that is proposed by nature for solving problems of data mining and especially for cluster analysis. Opportunities are examined for applying the oscillatory networks for general problems of cluster analysis. Have shown general features compared with various traditional methods for cluster analysis.\",\"PeriodicalId\":315574,\"journal\":{\"name\":\"2017 XX IEEE International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 XX IEEE International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCM.2017.7970526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 XX IEEE International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCM.2017.7970526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cluster analysis problems and bio-inspired clustering methods
The article presents the analysis of the clustering problem formalization and considers possibilities to use the classical methods and bio-inspired methods for solving problems of the cluster analysis. In this paper we do not present full review of the new clustering methods, but identify some trends in the development of cluster analysis and special attention is given to area of bio-inspired methods for clustering. Oscillatory networks can be considered as way that is proposed by nature for solving problems of data mining and especially for cluster analysis. Opportunities are examined for applying the oscillatory networks for general problems of cluster analysis. Have shown general features compared with various traditional methods for cluster analysis.