{"title":"进化模糊线性回归树","authors":"A. Lemos, W. Caminhas, F. Gomide","doi":"10.1109/FUZZY.2010.5583970","DOIUrl":null,"url":null,"abstract":"This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared against alternative evolving fuzzy models and classic models with fixed structures. The results suggest that evolving fuzzy regression tree is a promising approach for adaptive system modeling.","PeriodicalId":377799,"journal":{"name":"International Conference on Fuzzy Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Evolving fuzzy linear regression trees\",\"authors\":\"A. Lemos, W. Caminhas, F. Gomide\",\"doi\":\"10.1109/FUZZY.2010.5583970\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared against alternative evolving fuzzy models and classic models with fixed structures. The results suggest that evolving fuzzy regression tree is a promising approach for adaptive system modeling.\",\"PeriodicalId\":377799,\"journal\":{\"name\":\"International Conference on Fuzzy Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Fuzzy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZY.2010.5583970\",\"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 on Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.2010.5583970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared against alternative evolving fuzzy models and classic models with fixed structures. The results suggest that evolving fuzzy regression tree is a promising approach for adaptive system modeling.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
