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Open AccessArticle

Some Similarity Measures for Interval-Valued Picture Fuzzy Sets and Their Applications in Decision Making

1
School of Economics and Management, Civil Aviation University of China, Tianjin 300300, China
2
School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan 250014, China
3
Department of Mathematics and Statistics, International Islamic University, Islamabad 44000, Pakistan
*
Author to whom correspondence should be addressed.
Information 2019, 10(12), 369; https://doi.org/10.3390/info10120369
Received: 30 October 2019 / Revised: 23 November 2019 / Accepted: 23 November 2019 / Published: 25 November 2019
(This article belongs to the Special Issue Big Data Analytics and Computational Intelligence)
Similarity measures, distance measures and entropy measures are some common tools considered to be applied to some interesting real-life phenomena including pattern recognition, decision making, medical diagnosis and clustering. Further, interval-valued picture fuzzy sets (IVPFSs) are effective and useful to describe the fuzzy information. Therefore, this manuscript aims to develop some similarity measures for IVPFSs due to the significance of describing the membership grades of picture fuzzy set in terms of intervals. Several types cosine similarity measures, cotangent similarity measures, set-theoretic and grey similarity measures, four types of dice similarity measures and generalized dice similarity measures are developed. All the developed similarity measures are validated, and their properties are demonstrated. Two well-known problems, including mineral field recognition problems and multi-attribute decision making problems, are solved using the newly developed similarity measures. The superiorities of developed similarity measures over the similarity measures of picture fuzzy sets, interval-valued intuitionistic fuzzy sets and intuitionistic fuzzy sets are demonstrated through a comparison and numerical examples.
Keywords: similarity measures; interval-valued picture fuzzy sets; pattern recognition; multi-attribute decision making similarity measures; interval-valued picture fuzzy sets; pattern recognition; multi-attribute decision making
MDPI and ACS Style

Liu, P.; Munir, M.; Mahmood, T.; Ullah, K. Some Similarity Measures for Interval-Valued Picture Fuzzy Sets and Their Applications in Decision Making. Information 2019, 10, 369.

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