Fuzzy Convex Structures and Some Related Topics, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1068

Special Issue Editors


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Guest Editor
School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 102488, China
Interests: fuzzy convex structures; fuzzy topology; fuzzy matroid; fuzzy algebra
Special Issues, Collections and Topics in MDPI journals
School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 102488, China
Interests: fuzzy convex structures; fuzzy topology; fuzzy convergence; fuzzy rough set
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since Zadeh introduced the concept of fuzzy sets, fuzzy set theory has been applied to many research areas, including both theoretical and applied research. In this Special Issue, we will focus on the theory of fuzzy convex structures and related topics such as fuzzy set theory and theories that are related to convexity theory. From a theoretical standpoint, this Special Issue will cover fuzzy convex structures, fuzzy topological structures, fuzzy matroids and fuzzy algebra. From an applied standpoint, it will concentrate on fuzzy convex optimizations, fuzzy games, fuzzy data envelopes and fuzzy rough sets.

Prof. Dr. Fu-Gui Shi
Dr. Bin Pang
Guest Editors

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Keywords

  • fuzzy convex structures
  • fuzzy topology
  • fuzzy metric
  • fuzzy algebra
  • fuzzy order
  • fuzzy matroid
  • fuzzy game
  • fuzzy graphs
  • fuzzy rough set
  • fuzzy clustering
  • fuzzy data envelope

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Published Papers (2 papers)

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Research

19 pages, 333 KiB  
Article
Bi-Fuzzy S-Approximation Spaces
by Ronghai Wang, Xiaojie Xie and Huilai Zhi
Mathematics 2025, 13(2), 324; https://doi.org/10.3390/math13020324 - 20 Jan 2025
Viewed by 349
Abstract
The S-approximation spaces are significant extension of the rough set model and have been widely applied in intelligent decision-making. However, traditional S-approximation spaces are limited to two crisp universes, whereas bi-fuzzy universes (i.e., two distinct fuzzy domains) are more prevalent in practical applications. [...] Read more.
The S-approximation spaces are significant extension of the rough set model and have been widely applied in intelligent decision-making. However, traditional S-approximation spaces are limited to two crisp universes, whereas bi-fuzzy universes (i.e., two distinct fuzzy domains) are more prevalent in practical applications. To bridge this gap, this study introduces the bi-fuzzy S-approximation spaces (BFS approximation spaces) as an advancement of knowledge space theory’s fuzzy extension. Upper and lower approximation operators are formally defined, and the properties of BFS approximation spaces under various operations, such as complement, intersection and union are systematically explored. Special attention is given to a significant form of these operators, under which the monotonicity and complementary compatibility of BFS approximation spaces are rigorously analyzed. These results not only extend the theoretical framework of S-approximation spaces but also pave the way for further exploration of fuzzy extensions within knowledge space theory. Full article
(This article belongs to the Special Issue Fuzzy Convex Structures and Some Related Topics, 2nd Edition)
14 pages, 239 KiB  
Article
Fuzzy Hilbert Transform of Fuzzy Functions
by Zhibo Yan
Mathematics 2025, 13(2), 289; https://doi.org/10.3390/math13020289 - 17 Jan 2025
Viewed by 343
Abstract
This paper studies the properties of the Fourier transform of the fuzzy function, and extends the classical Poisson integral formula on the half plane to the fuzzy case, obtaining the composition of the fuzzy set generated by a point in the complex field [...] Read more.
This paper studies the properties of the Fourier transform of the fuzzy function, and extends the classical Poisson integral formula on the half plane to the fuzzy case, obtaining the composition of the fuzzy set generated by a point in the complex field under the action of the fuzzy function. Further, we define and study the fuzzy Hilbert transform of fuzzy functions and their properties. We prove that when the fuzzy function degenerates to the classical case, the fuzzy Hilbert transform will degenerate to the classical Hilbert transform, which proves that the fuzzy Hilbert transform is an extension of classical transformations in the fuzzy function space. In addition, we point out and prove some properties of the fuzzy Hilbert transform. For some fuzzy functions that meet certain requirements, their fuzzy Hilbert transform is a fuzzy point on 0. Full article
(This article belongs to the Special Issue Fuzzy Convex Structures and Some Related Topics, 2nd Edition)
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