Paper Info
Title
A new distance for intuitionistic fuzzy sets based on similarity matrix
Abstract
Measuring the distance between two intuitionistic fuzzy sets (IFSs) is an open issue. Many types of distances for the IFSs have been proposed in previous studies. Some existing methods cannot satisfy the axioms of similarity or provide counterintuitive cases. Others ignore the relationship between three parameters characterizing the information carried by the IFS. To address these issues, a new distance is proposed by analyzing the similarity among the three parameters of the IFS. The comparison with some existing distances illustrates that the new distance has a higher sensitivity and can effectively measure the similarity between the IFSs. The results of the application of pattern recognition are also shown that the proposed method has better recognition ability.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2919521
IEEE ACCESS
Keywords
Field
DocType
Intuitionistic fuzzy set,distance function,similarity measure,pattern recognition,medical diagnosis
Counterintuitive,Pattern recognition,Similarity measure,Computer science,Axiom,Metric (mathematics),Fuzzy set,Artificial intelligence,Medical diagnosis,Similarity matrix,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
2
PageRank 
References 
Authors
0.36
0
3
Name
Order
Citations
PageRank
Cuiping Cheng172.05
Fuyuan Xiao220119.11
Ze-Hong Cao39615.40