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Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science

Submission Deadline: 15 February 2022 (closed)

Guest Editors

Prof. Jun Ye, Ningbo University, China
Prof. Yanhui Guo, University of Illinois at Springfield, USA


There exist the vagueness and uncertainty of human judgments and cognitions regarding complicated real-world problems. Aiming at the practical problems of uncertainty and incompleteness, the fuzzy set proposed by Zadeh has been widely used in various fields. Due to the need for better and detailed membership functions in real science and engineering problems, the classical fuzzy sets have been extended to type-2 fuzzy sets, hesitant fuzzy sets, multi-valued fuzzy sets, cubic sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, spherical fuzzy sets, neutrosophic sets, etc. Each of them is gaining significant attention in science and engineering areas. Then, these fuzzy set theories have been used in decision making, artificial intelligence, image processing, medical diagnosis, fault diagnosis, optimization design/programming, clustering analysis, big and small data mining, engineering modeling and analysis, etc. In recent years, various fuzzy set theories have made new progress and achievements in the engineering and scientific fields.

The focus of this special issue is the extension, modeling and applications of fuzzy set theory to solve engineering and scientific problems. Articles submitted to this special issue can also be concerned with various fuzzy set theories, modeling, and applications in decision making, artificial intelligence, big and small data mining, pattern recognition, information processing, medical diagnosis, faulty diagnosis, image processing, and many other practical modeling and analysis, etc. We invite researchers to contribute original research articles and review articles, which will stimulate continuous research on various fuzzy set theories, modeling and applications to evaluate/solve engineering and scientific problems.


Fuzzy set extension; Modeling and analysis; Engineering and scientific applications

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