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Fermatean fuzzy linguistic set and its application in multicriteria decision making
Author(s) -
Liu Donghai,
Liu Yuanyuan,
Chen Xiaohong
Publication year - 2019
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.22079
Subject(s) - ranking (information retrieval) , operator (biology) , fuzzy logic , term (time) , measure (data warehouse) , mathematics , fuzzy number , fuzzy set , membership function , set (abstract data type) , fuzzy set operations , computer science , artificial intelligence , score , fuzzy classification , function (biology) , linguistics , data mining , machine learning , biochemistry , chemistry , physics , philosophy , repressor , quantum mechanics , evolutionary biology , biology , transcription factor , gene , programming language
In this paper, we propose the concept of Fermatean fuzzy linguistic term sets based on linguistic term sets and Fermatean fuzzy sets. The basic operational laws, the score function, and the accuracy function of Fermatean fuzzy linguistic numbers are provided. Then we propose the Fermatean fuzzy linguistic weighted aggregation operator, the Fermatean fuzzy linguistic weighted geometric operator, and the Fermatean fuzzy linguistic distance measures. Furthermore, we extend the TOPSIS method to the proposed distance measures, and the ranking of alternatives is obtained under a Fermatean fuzzy linguistic environment. An example is provided to illustrate the feasibility and effectiveness of the proposed method, and a comparison with the existing method is also analyzed. Finally, the sensitivity analysis of the parameter λ in the proposed distance measure is also discussed.