{"title":"一种考虑数据结构的融合轴模糊建模方法","authors":"Kosuke Yamamoto, T. Yoshikawa, T. Furuhashi","doi":"10.1109/FUZZ.2003.1209387","DOIUrl":null,"url":null,"abstract":"Fuzzy modeling is known as one of the effective methods to identify unknown non-linear input-output relationships. In gathering information from constructed models or constructing models from known information, the model's understandability becomes essential. This paper defines new axes by fitting distributed data in input space and proposes a fuzzy modeling method considering data structure. This paper calls these axes, \"fusion axes\". The effectiveness of the proposed method is shown through some numerical experiments.","PeriodicalId":212172,"journal":{"name":"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A proposal of fuzzy modeling on fusion axes considering the data structure\",\"authors\":\"Kosuke Yamamoto, T. Yoshikawa, T. Furuhashi\",\"doi\":\"10.1109/FUZZ.2003.1209387\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy modeling is known as one of the effective methods to identify unknown non-linear input-output relationships. In gathering information from constructed models or constructing models from known information, the model's understandability becomes essential. This paper defines new axes by fitting distributed data in input space and proposes a fuzzy modeling method considering data structure. This paper calls these axes, \\\"fusion axes\\\". The effectiveness of the proposed method is shown through some numerical experiments.\",\"PeriodicalId\":212172,\"journal\":{\"name\":\"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.\",\"volume\":\"97 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZ.2003.1209387\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZ.2003.1209387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A proposal of fuzzy modeling on fusion axes considering the data structure
Fuzzy modeling is known as one of the effective methods to identify unknown non-linear input-output relationships. In gathering information from constructed models or constructing models from known information, the model's understandability becomes essential. This paper defines new axes by fitting distributed data in input space and proposes a fuzzy modeling method considering data structure. This paper calls these axes, "fusion axes". The effectiveness of the proposed method is shown through some numerical experiments.