Studies on Consistency Measure of Hesitant Fuzzy Preference Relations | Zendy

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Studies on Consistency Measure of Hesitant Fuzzy Preference Relations

Author(s) -

Bin Zhu

Publication year - 2013

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2013.05.059

Subject(s) - consistency (knowledge bases) , computer science , preference , measure (data warehouse) , fuzzy logic , extension (predicate logic) , fuzzy set , set (abstract data type) , data mining , hfss , membership function , artificial intelligence , mathematics , statistics , telecommunications , microstrip antenna , antenna (radio) , programming language

Hesitant fuzzy sets (HFSs), as an extension of fuzzy sets, consider the degrees of membership by a set of possible values rather than a single one. For further applications of HFSs to decision making, we develop a concept of hesitant fuzzy preference relations (HFPRs) as a tool to collect and present decision makers’ (DMs) preferences. Due to the importance of consistency measure for HFPRs to ensure that DMs are being neither random nor illogical, we develop a regression method to transform HFPRs to fuzzy preference relations (FPRs) with the highest consistency level. Some examples are given for illustration

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