@inproceedings{9b7500aa17474563a93ef0f5d1a29b1e,
title = "New entropy and distance measures of intuitionistic fuzzy sets",
abstract = "In fuzzy set theory, the distance and entropy measure of intuitionistic fuzzy sets (IFSs) have received extensive concern because of the capability for handling imprecise or uncertain problems. However, most of the existing modeling methods for distance and entropy measure are imperfect in teams of intelligibility and performance. In this work, we proposed a new geometric modeling method that can be simultaneously used for distance and fuzzy entropy modeling of IFSs. We used rigorously mathematical derivation to prove that the proposed distance and fuzzy entropy measures satisfy the properties of the definitions. In the experiments, we applied the proposed distance and fuzzy entropy measure into pattern recognition, medical diagnosis, and multi-attribute decision making to examine the usability of the two measures in practical situations.",
keywords = "Distance measure, Entropy, Intuitionistic fuzzy set, Medical diagnosis, Multi-attribute decision making, Pattern recognition",
author = "Jinfang Huang and Xin Jin and Dianwu Fang and Lee, {Shin Jye} and Qian Jiang and Shaowen Yao",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; null ; Conference date: 19-07-2020 Through 24-07-2020",
year = "2020",
month = jul,
doi = "10.1109/FUZZ48607.2020.9177690",
language = "English",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020 - Proceedings",
address = "United States",
}