Recent Advances in Fuzzy Theory Applications

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 525

Special Issue Editors


E-Mail Website1 Website2
Guest Editor
School of Engineering and Architecture of Fribourg, HES-SO University of Applied Sciences and Arts of Western Switzerland, 1700 Fribourg, Switzerland
Interests: fuzzy statistics; uncertainty modelling; fuzzy sets and systems; fuzzy inference systems; fuzzy decision-making; statistical and mathematical modelling; survey statistics; applied statistics

E-Mail Website
Guest Editor
Department of Statistics and Operational Research, University of Cadiz, 11003 Cádiz, Spain
Interests: optimization methods under uncertainty; interval and fuzzy numbers; multi-objective programming; generalized convexity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, fuzzy theory has demonstrated its tremendous potential to address complex and uncertain systems across diverse domains. By modelling imprecise, ambiguous, or vague data, fuzzy logic and its extensions have paved the way for innovative solutions in computational intelligence, decision-making, and data analysis. This Special Issue, entitled “Recent Advances in Fuzzy Theory Applications”, seeks to highlight state-of-the-art research contributions and practical implementations and developments of fuzzy theory in real-world scenarios. We invite researchers, practitioners, and experts to submit original research articles, comprehensive reviews, and cutting-edge applications that contribute to advancing fuzzy theory. The focus will be on novel methodologies, interdisciplinary approaches, innovative applications, and emerging trends in fuzzy logic and systems. This Special Issue covers a broad spectrum of topics, including, but not limited to, the following:

  • Fuzzy Systems and Models
    • Fuzzy set theory and extensions;
    • Interval-valued fuzzy systems and applications;
    • Fuzzy mathematical modelling and optimisation.
  • Fuzzy Decision-Making
    • Multi-criteria decision-making under uncertainty;
    • Fuzzy game theory and bargaining models;
    • Fuzzy logic in economics and business analytics.
  • Computational Intelligence with Fuzzy Techniques
    • Fuzzy neural networks and hybrid systems;
    • Fuzzy clustering, pattern recognition, and machine learning;
    • Evolutionary and swarm algorithms with fuzzy logic.
  • Applications in Engineering and Technology
    • Fuzzy control systems and robotics;
    • Intelligent transportation systems;
    • Smart grids, renewable energy, and environmental monitoring.
  • Fuzzy Statistics and Uncertainty Modelling
    • Statistical analysis with fuzzy data;
    • Fuzzy regression, hypothesis testing, and forecasting;
    • Applications of fuzzy statistics in big data and machine learning.
  • Emerging Interdisciplinary Applications
    • Fuzzy logic in healthcare and medical diagnosis, or any relevant field;
    • Fuzzy-based natural language processing and text mining;
    • Applications in education, social sciences, and psychology.
  • Advances in Fuzzy Software and Tools
    • Development of fuzzy logic-based software systems;
    • Simulation and visualisation tools for fuzzy systems;
    • Integration of fuzzy techniques with big data and IoT.

Dr. Rédina Berkachy
Prof. Dr. Manuel Arana-Jimenez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Axioms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computational intelligence
  • fuzzy logic
  • fuzzy decision-making
  • fuzzy mathematics
  • fuzzy optimisation
  • fuzzy set theory
  • fuzzy statistics
  • fuzzy theory applications
  • uncertainty modelling
  • fuzzy systems and models

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

22 pages, 827 KiB  
Article
Fuzzy Clustering Based on Activity Sequence and Cycle Time in Process Mining
by Onur Dogan and Hunaıda Avvad
Axioms 2025, 14(5), 351; https://doi.org/10.3390/axioms14050351 - 4 May 2025
Viewed by 69
Abstract
Clustering plays a vital role in process mining as it organizes complex event logs into meaningful groups, helping to identify common patterns, outliers, and inefficiencies. This simplification enables organizations to detect bottlenecks and optimize workflows by uncovering trends and variations that might otherwise [...] Read more.
Clustering plays a vital role in process mining as it organizes complex event logs into meaningful groups, helping to identify common patterns, outliers, and inefficiencies. This simplification enables organizations to detect bottlenecks and optimize workflows by uncovering trends and variations that might otherwise remain hidden. Fuzzy clustering addresses the challenge of overlapping behaviors, providing actionable insights for targeted improvements and enhanced operational efficiency. Nevertheless, conventional clustering algorithms for process mining focus either on activity sequences or cycle times, resulting in incomplete insights due to the neglect of temporal or structural variations. This work introduces a new fuzzy clustering methodology that incorporates both activity sequences and cycle times through a weighted distance metric. The proposed approach balances the weights of similarity in sequences as well as time variation flexibly using the parameter α, enabling clusters to represent both structural as well as performance-based process attributes. Through using fuzzy C-means clustering, the method allows cases to have multiple memberships with different membership degrees, providing flexibility regarding overlapping process behavior. An experimental evaluation using real-life event logs demonstrates the effectiveness of the method in discerning process variants. It yields superior results compared to conventional methods that account for only sequence-based clustering scenarios, as well as time-based clustering methods. The results describe the significant importance of optimizing clustering results by varying α, where a balanced weighting (α=0.5) gives more meaningful clusters. Ultimately, the framework enhances process mining by offering detailed insights for analyzing operational inefficiencies, bottlenecks, and resource allocation mismatches, providing substantial real-world benefits for industries that demand effective process improvement. Full article
(This article belongs to the Special Issue Recent Advances in Fuzzy Theory Applications)
Show Figures

Figure 1

Back to TopTop