Open AccessOn Some Knowledge Measures of Intuitionistic Fuzzy Sets of Type Two with Application to MCDM
Author(s) -
Surender Singh,
Sumita Lalotra,
Abdul Haseeb Ganie
Publication year - 2020
Publication title -
cybernetics and information technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.272
H-Index - 17
eISSN - 1314-4081
pISSN - 1311-9702
DOI - 10.2478/cait-2020-0001
Subject(s) - ambiguity , computer science , multiple criteria decision analysis , entropy (arrow of time) , measure (data warehouse) , mathematics , data mining , mathematical optimization , physics , quantum mechanics , programming language
To overcome the certain limitations of Intuitionistic Fuzzy Sets (IFSs), the notion of Intuitionistic Fuzzy Sets of Second Type (IFSST) was introduced. IFSST is a modified version of IFS for handling some problems in a reasonable manner. Type two Intuitionistic Fuzzy entropy (IFSST-entropy) measures the amount of ambiguity/uncertainty present in an IFSST. In the present paper, we introduce the concept of dual measure of IFSST-entropy, i.e., IFSST-knowledge measure. We develop some IFSST-knowledge measures and prove some of their properties. We also show the superiority of the proposed IFSST-knowledge measures through comparative study. Further, we demonstrate the application of the proposed knowledge measures in Multi-Criteria Decision-Making (MCDM).