{"title":"mamdani型与sugeno型模糊推理系统诊断糖尿病的比较研究","authors":"Jimmy Singla","doi":"10.1109/ICACEA.2015.7164799","DOIUrl":null,"url":null,"abstract":"Fuzzy inference systems for diagnosis of diabetes are developed using Mamdani-type and Sugeno-type fuzzy models. The outcome obtained by two fuzzy inference systems is evaluated. This paper summarizes the essential variation among the Mamdani-type and Sugeno-type fuzzy inference systems. MATLAB fuzzy logic toolbox is used for the simulation of both the models. This also confirms which one is a superior choice of the two fuzzy inference systems for diagnosis of diabetes.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"08 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":"{\"title\":\"Comparative study of Mamdani-type and Sugeno-type fuzzy inference systems for diagnosis of diabetes\",\"authors\":\"Jimmy Singla\",\"doi\":\"10.1109/ICACEA.2015.7164799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy inference systems for diagnosis of diabetes are developed using Mamdani-type and Sugeno-type fuzzy models. The outcome obtained by two fuzzy inference systems is evaluated. This paper summarizes the essential variation among the Mamdani-type and Sugeno-type fuzzy inference systems. MATLAB fuzzy logic toolbox is used for the simulation of both the models. This also confirms which one is a superior choice of the two fuzzy inference systems for diagnosis of diabetes.\",\"PeriodicalId\":202893,\"journal\":{\"name\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"volume\":\"08 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACEA.2015.7164799\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advances in Computer Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACEA.2015.7164799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative study of Mamdani-type and Sugeno-type fuzzy inference systems for diagnosis of diabetes
Fuzzy inference systems for diagnosis of diabetes are developed using Mamdani-type and Sugeno-type fuzzy models. The outcome obtained by two fuzzy inference systems is evaluated. This paper summarizes the essential variation among the Mamdani-type and Sugeno-type fuzzy inference systems. MATLAB fuzzy logic toolbox is used for the simulation of both the models. This also confirms which one is a superior choice of the two fuzzy inference systems for diagnosis of diabetes.