Open AccessNovel Distance Measures for Single-Valued Neutrosophic Fuzzy Sets and Their Applications to Multicriteria Group Decision-Making Problem
Author(s) -
Yun Jin,
Muhammad Kamran,
Nadeem Salamat,
Shouzhen Zeng,
Riaz Hussain Khan
Publication year - 2022
Publication title -
journal of function spaces
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 28
eISSN - 2314-8896
pISSN - 2314-8888
DOI - 10.1155/2022/7233420
Subject(s) - ranking (information retrieval) , group decision making , fuzzy logic , mathematics , focus (optics) , data mining , algorithm , artificial intelligence , computer science , psychology , optics , social psychology , physics
Single-valued neutrosophic sets are a hybrid of fuzzy sets that are used to represent uncertain, imprecise, partial, and inconsistent information in the actual world. The focus of this research is to develop two novel distance measures for single-valued neutrosophic fuzzy sets (SVNFSs). We introduced two new distance measures named d η G , Y and d ζ G , Y for SVNFSs and apply these measures to different examples and also compare them with existing measures to show the validity of our proposed measures. Our results are reliable and useful for decision-making problems. We also proposed an algorithm for multicriteria group decision-making. Based on this algorithm, we find the ranking matrices using proposed distance measures. We also give an example to demonstrate the notion and concept of our algorithm.