{"title":"用描述词和真实词进行计算","authors":"I. Turksen","doi":"10.1109/NAFIPS.1999.781643","DOIUrl":null,"url":null,"abstract":"Computing with words [Zadeh, 1995] is fundamental to our understanding the foundation of fuzzy theory. Naturally, there are a large variety of \"words\" that we need to recognize and utilize in our computational paradigms. However, descriptive and veristic words are essential for the fundamental derivation of fuzzy set and logic formulas. Descriptive linguistic terms help us assign an element to a fuzzy set with a membership value. Whereas the veristic words determine the degree of truthhood associated with a descriptive membership value. Understanding this distinction between descriptive and veristic linguistic terms form the basis of deriving the normal forms of fuzzy set and logic formulas. Within this perspective, there are potentially four possible fuzzy set and logic theories. Each of these has their own unique formulas. Most of the current literature is based on a \"myopic\" theory which is an approximation of the fuzzy set and two-valued logic based formalism. These issues are presented in our attempt toward restructuring the foundations of fuzzy theory.","PeriodicalId":335957,"journal":{"name":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Computing with descriptive and veristic words\",\"authors\":\"I. Turksen\",\"doi\":\"10.1109/NAFIPS.1999.781643\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computing with words [Zadeh, 1995] is fundamental to our understanding the foundation of fuzzy theory. Naturally, there are a large variety of \\\"words\\\" that we need to recognize and utilize in our computational paradigms. However, descriptive and veristic words are essential for the fundamental derivation of fuzzy set and logic formulas. Descriptive linguistic terms help us assign an element to a fuzzy set with a membership value. Whereas the veristic words determine the degree of truthhood associated with a descriptive membership value. Understanding this distinction between descriptive and veristic linguistic terms form the basis of deriving the normal forms of fuzzy set and logic formulas. Within this perspective, there are potentially four possible fuzzy set and logic theories. Each of these has their own unique formulas. Most of the current literature is based on a \\\"myopic\\\" theory which is an approximation of the fuzzy set and two-valued logic based formalism. These issues are presented in our attempt toward restructuring the foundations of fuzzy theory.\",\"PeriodicalId\":335957,\"journal\":{\"name\":\"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.1999.781643\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.1999.781643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computing with words [Zadeh, 1995] is fundamental to our understanding the foundation of fuzzy theory. Naturally, there are a large variety of "words" that we need to recognize and utilize in our computational paradigms. However, descriptive and veristic words are essential for the fundamental derivation of fuzzy set and logic formulas. Descriptive linguistic terms help us assign an element to a fuzzy set with a membership value. Whereas the veristic words determine the degree of truthhood associated with a descriptive membership value. Understanding this distinction between descriptive and veristic linguistic terms form the basis of deriving the normal forms of fuzzy set and logic formulas. Within this perspective, there are potentially four possible fuzzy set and logic theories. Each of these has their own unique formulas. Most of the current literature is based on a "myopic" theory which is an approximation of the fuzzy set and two-valued logic based formalism. These issues are presented in our attempt toward restructuring the foundations of fuzzy theory.