Publication | Open Access
Logic connectives of complex fuzzy sets
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2018
Year
Unknown Venue
EngineeringFuzzy ModelingDiagnosisSemanticsData ScienceData MiningLogic ConnectivesMany-valued LogicBiostatisticsComplex FuzzyPublic HealthFuzzy Pattern RecognitionFuzzy LogicFuzzy ComputingComplex Fuzzy SetsFuzzy MathematicsFuzzy Expert SystemComplex T-normsHealth Informatics
The Fuzzy Set Theory has been applied in various problems in numerous fields. In particular, the concepts of t-norms and t-conorms serve a significant role in shaping the theory and its applications. The notion of Complex Fuzzy Sets extends the Fuzzy Set Theory and provides several advantages over the classical theory, especially in terms of the capability to concisely, efficiently, and accurately represent complex relations between fuzzy set components. Some of the areas where complex fuzzy sets have been successfully applied are the areas of time series analysis and multi-criteria decision making problems. The notions of complex t-norms and t-conorms have not been fully developed so far. In this paper, we present the complex fuzzy set forms of t-norms and t-conorms and detail their properties. Additionally, we provide two numerical examples of applying the complex t-norm and tconorm to multi-criteria decision making in the context of medicine- related problems using medical datasets.