{"title":"人工免疫系统中自我-非自我检测的检测器生成算法","authors":"Mridul Goswami, Anirban Bhattacharjee","doi":"10.1109/I2CT.2014.7092107","DOIUrl":null,"url":null,"abstract":"In this paper a new algorithm for detector generation for self-nonself detection in Artificial Immune System is presented. The algorithm is inspired from the Negative Selection process of T cell maturation process in Biological Immune System. This algorithm is applicable where data are represented in the form of strings. R-chunk matching rule is used while checking two strings whether match or not. The algorithm is analyzed and compared with other relevant existing algorithms for detector generation.","PeriodicalId":384966,"journal":{"name":"International Conference for Convergence for Technology-2014","volume":"59 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Detector generation algorithm for self-nonself detection in Artificial Immune System\",\"authors\":\"Mridul Goswami, Anirban Bhattacharjee\",\"doi\":\"10.1109/I2CT.2014.7092107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a new algorithm for detector generation for self-nonself detection in Artificial Immune System is presented. The algorithm is inspired from the Negative Selection process of T cell maturation process in Biological Immune System. This algorithm is applicable where data are represented in the form of strings. R-chunk matching rule is used while checking two strings whether match or not. The algorithm is analyzed and compared with other relevant existing algorithms for detector generation.\",\"PeriodicalId\":384966,\"journal\":{\"name\":\"International Conference for Convergence for Technology-2014\",\"volume\":\"59 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference for Convergence for Technology-2014\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I2CT.2014.7092107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference for Convergence for Technology-2014","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2CT.2014.7092107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detector generation algorithm for self-nonself detection in Artificial Immune System
In this paper a new algorithm for detector generation for self-nonself detection in Artificial Immune System is presented. The algorithm is inspired from the Negative Selection process of T cell maturation process in Biological Immune System. This algorithm is applicable where data are represented in the form of strings. R-chunk matching rule is used while checking two strings whether match or not. The algorithm is analyzed and compared with other relevant existing algorithms for detector generation.
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