Chunmei Chang, Hongmei Lin, Qiuting Wang, Xuehui Hou, Yefei Zhang, L. Zou
{"title":"基于语言有序对三元组的模糊推理方法","authors":"Chunmei Chang, Hongmei Lin, Qiuting Wang, Xuehui Hou, Yefei Zhang, L. Zou","doi":"10.1109/ISKE47853.2019.9170325","DOIUrl":null,"url":null,"abstract":"With the rapid development of artificial intelligence, it is of significance in practical application to reasoning in uncertain environment and to make judgment and reasonable decision on this basis. In order to deal with the multiple class data in uncertain environment, we standardize it and convert it into linguistic ordered pair 3-tuple which can describe the linguistic values from both positive and negative aspects, so as to obtain more reasonable reasoning results. Based on the linguistic 2-tuple, this paper constructs a standardized transformation model between the interval-valued fuzzy set and linguistic ordered pair 3-tuple by defining the transformation operator, which solves the problem of data standardization of this type. Furthermore, aiming at the problem of reasoning in uncertain linguistic environment, four operators of linguistic ordered pair 3-tuple are proposed and their properties are discussed. At the same time, in order to increase the credibility of linguistic ordered pair 3-tuple reasoning, we present a reasoning model of linguistic ordered pair 3-tuple combined with the similarity between the rules of linguistic ordered pair 3-tuple. Finally, an example which concerned the intelligent case system is given to illustrate the effectiveness and rationality of the proposed method.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Approach of Fuzzy Reasoning Based on Linguistic Ordered Pair 3-tuple\",\"authors\":\"Chunmei Chang, Hongmei Lin, Qiuting Wang, Xuehui Hou, Yefei Zhang, L. Zou\",\"doi\":\"10.1109/ISKE47853.2019.9170325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of artificial intelligence, it is of significance in practical application to reasoning in uncertain environment and to make judgment and reasonable decision on this basis. In order to deal with the multiple class data in uncertain environment, we standardize it and convert it into linguistic ordered pair 3-tuple which can describe the linguistic values from both positive and negative aspects, so as to obtain more reasonable reasoning results. Based on the linguistic 2-tuple, this paper constructs a standardized transformation model between the interval-valued fuzzy set and linguistic ordered pair 3-tuple by defining the transformation operator, which solves the problem of data standardization of this type. Furthermore, aiming at the problem of reasoning in uncertain linguistic environment, four operators of linguistic ordered pair 3-tuple are proposed and their properties are discussed. At the same time, in order to increase the credibility of linguistic ordered pair 3-tuple reasoning, we present a reasoning model of linguistic ordered pair 3-tuple combined with the similarity between the rules of linguistic ordered pair 3-tuple. Finally, an example which concerned the intelligent case system is given to illustrate the effectiveness and rationality of the proposed method.\",\"PeriodicalId\":399084,\"journal\":{\"name\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISKE47853.2019.9170325\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE47853.2019.9170325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Approach of Fuzzy Reasoning Based on Linguistic Ordered Pair 3-tuple
With the rapid development of artificial intelligence, it is of significance in practical application to reasoning in uncertain environment and to make judgment and reasonable decision on this basis. In order to deal with the multiple class data in uncertain environment, we standardize it and convert it into linguistic ordered pair 3-tuple which can describe the linguistic values from both positive and negative aspects, so as to obtain more reasonable reasoning results. Based on the linguistic 2-tuple, this paper constructs a standardized transformation model between the interval-valued fuzzy set and linguistic ordered pair 3-tuple by defining the transformation operator, which solves the problem of data standardization of this type. Furthermore, aiming at the problem of reasoning in uncertain linguistic environment, four operators of linguistic ordered pair 3-tuple are proposed and their properties are discussed. At the same time, in order to increase the credibility of linguistic ordered pair 3-tuple reasoning, we present a reasoning model of linguistic ordered pair 3-tuple combined with the similarity between the rules of linguistic ordered pair 3-tuple. Finally, an example which concerned the intelligent case system is given to illustrate the effectiveness and rationality of the proposed method.