{"title":"模糊分类规则的增量归纳","authors":"A. Bouchachia","doi":"10.1109/ESDIS.2009.4938996","DOIUrl":null,"url":null,"abstract":"The present paper presents an incremental fuzzy rule based system for classification purposes. Relying on fuzzy min-max neural networks, the present paper shows how fuzzy rules can be continuously online generated to meet the requirements of non-stationary dynamic environments. Simulation results are reported to show the effectiveness of the proposed approach.","PeriodicalId":257215,"journal":{"name":"2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Incremental induction of fuzzy classification rules\",\"authors\":\"A. Bouchachia\",\"doi\":\"10.1109/ESDIS.2009.4938996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper presents an incremental fuzzy rule based system for classification purposes. Relying on fuzzy min-max neural networks, the present paper shows how fuzzy rules can be continuously online generated to meet the requirements of non-stationary dynamic environments. Simulation results are reported to show the effectiveness of the proposed approach.\",\"PeriodicalId\":257215,\"journal\":{\"name\":\"2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESDIS.2009.4938996\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESDIS.2009.4938996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Incremental induction of fuzzy classification rules
The present paper presents an incremental fuzzy rule based system for classification purposes. Relying on fuzzy min-max neural networks, the present paper shows how fuzzy rules can be continuously online generated to meet the requirements of non-stationary dynamic environments. Simulation results are reported to show the effectiveness of the proposed approach.
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