Topic Editors

Department of Mathematics, National Kaohsiung Normal University, Kaohsiung 802, Taiwan
College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China
Dr. Rongrong Yu
School of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, China

Fuzzy Sets Theory and Its Applications

Abstract submission deadline
31 May 2026
Manuscript submission deadline
31 July 2026
Viewed by
311

Topic Information

Dear Colleagues,

The concept of fuzzy sets introduced by L.A. Zadeh in 1965 tried to extend the classical set theory. It is well-known that a classical set corresponds to an indicator function whose values are only taken to be 0 and 1. With the aid of membership functions associated with a fuzzy set, each element in a set allows one to take any values between 0 and 1 that can be treated as the degree of membership. This kind of imprecision draws forth a multitude of applications. This topic will focus on the original research that reflects the theoretical developments and applicable results.

The topics of interest include but are not limited to the following:

  • Foundation of fuzzy sets (fuzzy arithmetic operations, extension principle, possibility measures, etc.).
  • Fuzzy mathematics (fuzzy topology, fuzzy real analysis, fuzzy integral and differential equations, fuzzy metric spaces, fuzzy algebra, etc.). 
  • Fuzzy logics (many-valued logics, type-2 fuzzy logics, intuitionistic fuzzy logics, etc.). 
  • Fuzzy statistical analysis (fuzzy random variables, fuzzy regression analysis, fuzzy reliability analysis, fuzzy times series, fuzzy Markov process, etc.). 
  • Hybrid systems (fuzzy control, fuzzy neural networks, genetic fuzzy systems, fuzzy intelligent systems, fuzzy biomedical systems, fuzzy chaotic systems, fuzzy information systems, etc.). 
  • Nature of computation (ant colony optimization, artificial immune systems, genetic algorithms, particle swarm intelligence, simulated annealing, tabu search, etc.). 
  • Computational intelligence (artificial intelligence, approximate reasoning, expert systems, machine learning, support vector machines, robotics, image processing, pattern recognition, information retrieval, etc.). 
  • Operations research and management sciences (fuzzy games theory, fuzzy inventory models, fuzzy queueing theory, fuzzy scheduling problems, fuzzy optimization, fuzzy decision making, fuzzy data mining, fuzzy clustering, stochastic optimization, financial derivatives, uncertainty modeling, etc.).

Prof. Dr. Hsien-Chung Wu
Prof. Dr. Ziye Zhang
Dr. Rongrong Yu
Topic Editors

Keywords

  • fuzzy logic
  • extension principle
  • fuzzy arithmetic operations
  • fuzzy sets operations
  • fuzzy metric spaces
  • fixed point theorem
  • support functions

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Algorithms
algorithms
1.8 4.1 2008 18.9 Days CHF 1600 Submit
Axioms
axioms
1.9 - 2012 22.8 Days CHF 2400 Submit
Energies
energies
3.0 6.2 2008 16.8 Days CHF 2600 Submit
Mathematics
mathematics
2.3 4.0 2013 18.3 Days CHF 2600 Submit
Symmetry
symmetry
2.2 5.4 2009 17.3 Days CHF 2400 Submit

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Published Papers (1 paper)

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30 pages, 2525 KiB  
Article
A Dynamic Threat Assessment Method for Multi-Target Unmanned Aerial Vehicles at Multiple Time Points Based on Fuzzy Multi-Attribute Decision Making and Fuse Intention
by Qianru Niu, Shuangyin Ren, Wei Gao and Chunjiang Wang
Mathematics 2025, 13(10), 1663; https://doi.org/10.3390/math13101663 - 19 May 2025
Viewed by 153
Abstract
In response to the threat assessment challenge posed by unmanned aerial vehicles (UAVs) in air defense operations, this paper proposes a dynamic assessment model grounded in fuzzy multi-attribute decision making. First, a three-dimensional evaluation index system is established, encompassing capability, opportunity, and intention. [...] Read more.
In response to the threat assessment challenge posed by unmanned aerial vehicles (UAVs) in air defense operations, this paper proposes a dynamic assessment model grounded in fuzzy multi-attribute decision making. First, a three-dimensional evaluation index system is established, encompassing capability, opportunity, and intention. Quantification functions for assessing the threat level of each attribute are then designed. To account for the temporal dynamics of the battlefield, an innovative fusion approach is developed, integrating inverse Poisson distribution time weights with subjective–objective comprehensive weighting, thereby establishing a dynamic variable weight fusion mechanism. Among these, the subjective weights are determined by integrating the intention probability matrix, effectively incorporating the intentions into the threat assessment process to reflect their dynamic changes and enhancing the overall evaluation accuracy. Leveraging the improved technique for order preference by similarity to ideal solution (TOPSIS), the model achieves threat prioritization. Experimental results demonstrate that this method significantly enhances the reliability of threat assessments in uncertain and dynamic battlefield environments, offering valuable support for air defense command and control systems. Full article
(This article belongs to the Topic Fuzzy Sets Theory and Its Applications)
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