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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.

Item Type:	Refereed Article
Keywords:	intuitionistic fuzzy set, distance function, similarity measure, pattern recognition, medical diagnosis
Research Division:	Information and Computing Sciences
Research Group:	Machine learning
Research Field:	Neural networks
Objective Division:	Defence
Objective Group:	Defence
Objective Field:	Intelligence, surveillance and space
UTAS Author:	Cao, Z (Dr Zehong Cao)
ID Code:	133051
Year Published:	2019
Web of Science® Times Cited:	10
Deposited By:	Information and Communication Technology
Deposited On:	2019-06-04
Last Modified:	2020-05-18
Downloads:	13 View Download Statistics