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Cited by 377

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Pythagorean Fuzzy Information Measures and Their Applications

Open access
Peng, Xindong, Yuan, Huiyong, Yang, Yong·2017·International Journal of Intelligent Systems

Abstract

Pythagorean fuzzy set (PFS), originally proposed by Yager, is more capable than intuitionistic fuzzy set (IFS) to handle vagueness in the real world. The main purpose of this paper is to investigate the relationship between the distance measure, the similarity measure, the entropy, and the inclusion measure for PFSs. The primary goal of the study is to suggest the systematic transformation of information measures (distance measure, similarity measure, entropy, inclusion measure) for PFSs. For achieving this goal, some new formulae for information measures of PFSs are introduced. To show the efficiency of the proposed similarity measure, we apply it to pattern recognition, clustering analysis, and medical diagnosis. Some illustrative examples are given to support the findings and also demonstrate their practicality and effectiveness of similarity measure between PFSs.

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Metadata

Authors
Peng, X., Yuan, H., & Yang, Y.
Venue
International Journal of Intelligent Systems
Publisher
Wiley
Published
2017-02-20
Volume
32
Issue
10
Pages
991-1029
ISSN
0884-8173 (ISSN-L)
OpenAlex
W2589233777
Cited by
377
References
49
FWCI
35.79
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Pythagorean Fuzzy Information Measures and Their Applications. https://app.cochat.ai/papers/10.1002/int.21880
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Peng, X., Yuan, H., & Yang, Y. (2017). Pythagorean Fuzzy Information Measures and Their Applications. International Journal of Intelligent Systems. https://doi.org/10.1002/int.21880

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