Special Issues
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Fuzzy Logic: Next-Generation Algorithms and Applications

Submission Deadline: 15 November 2025 (closed) View: 24190 Submit to Special Issue

Guest Editors

Dr. Sukhjit Singh Sehra

Email: ssehra@wlu.ca

Affiliation:  Department of Computer Science, Wilfrid Laurier University, AWaterloo, ON N2L 3C5, Canada

Homepage:

Research Interests: machine learning, large language models, fuzzy logic, intelligent transportation systems

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Summary

This Special Issue, titled "Fuzzy Logic: Next-Generation Algorithms and Applications", aims to highlight cutting-edge interdisciplinary research that advances fuzzy logic methodologies and their transformative applications. We seek contributions that push the boundaries of fuzzy systems in key domains as following topics.

Next-Gen Fuzzy Algorithms:
Hybrid models integrating fuzzy logic with deep learning, reinforcement learning, or evolutionary computation.
Explainable AI (XAI) via interpretable fuzzy systems.
Scalable and high-performance fuzzy computing for big data.

Advanced Applications:
Fuzzy logic in autonomous systems (self-driving cars, drones, robotics).
AI-driven healthcare diagnostics and personalized medicine using fuzzy reasoning.
Smart cities, ITS, Industry 4.0, and IoT with adaptive fuzzy control.


Keywords

Artificial Intelligence, Fuzzy Logic, Computational Intelligence, Fuzzy Algorithms

Published Papers


  • Open Access

    ARTICLE

    An Innovative Semi-Supervised Fuzzy Clustering Technique Using Cluster Boundaries

    Duong Tien Dung, Ha Hai Nam, Nguyen Long Giang, Luong Thi Hong Lan
    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5341-5357, 2025, DOI:10.32604/cmc.2025.068299
    (This article belongs to the Special Issue: Fuzzy Logic: Next-Generation Algorithms and Applications)
    Abstract Active semi-supervised fuzzy clustering integrates fuzzy clustering techniques with limited labeled data, guided by active learning, to enhance classification accuracy, particularly in complex and ambiguous datasets. Although several active semi-supervised fuzzy clustering methods have been developed previously, they typically face significant limitations, including high computational complexity, sensitivity to initial cluster centroids, and difficulties in accurately managing boundary clusters where data points often overlap among multiple clusters. This study introduces a novel Active Semi-Supervised Fuzzy Clustering algorithm specifically designed to identify, analyze, and correct misclassified boundary elements. By strategically utilizing labeled data through active learning, our More >

  • Open Access

    REVIEW

    A Review of Artificial Intelligence-Enhanced Fuzzy Multi-Criteria Decision-Making Approaches for Sustainable Transportation Planning

    Nezir Aydin, Melike Cari, Betul Kara, Ertugrul Ayyildiz
    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2625-2650, 2025, DOI:10.32604/cmc.2025.067290
    (This article belongs to the Special Issue: Fuzzy Logic: Next-Generation Algorithms and Applications)
    Abstract Transportation systems are rapidly transforming in response to urbanization, sustainability challenges, and advances in digital technologies. This review synthesizes the intersection of artificial intelligence (AI), fuzzy logic, and multi-criteria decision-making (MCDM) in transportation research. A comprehensive literature search was conducted in the Scopus database, utilizing carefully selected AI, fuzzy, and MCDM keywords. Studies were rigorously screened according to explicit inclusion and exclusion criteria, resulting in 73 eligible publications spanning 2006–2025. The review protocol included transparent data extraction on methodological approaches, application domains, and geographic distribution. Key findings highlight the prevalence of hybrid fuzzy AHP and… More >

  • Open Access

    ARTICLE

    Computational Assessment of Energy Supply Sustainability Using Picture Fuzzy Choquet Integral Decision Support System

    Abrar Hussain, Hafiz Aftab Anwar, Kifayat Ullah, Dragan Pamucar, Vladimir Simic
    CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1311-1337, 2025, DOI:10.32604/cmc.2025.066569
    (This article belongs to the Special Issue: Fuzzy Logic: Next-Generation Algorithms and Applications)
    Abstract For any country, the availability of electricity is crucial to the development of the national economy and society. As a result, decision-makers and policy-makers can improve the sustainability and security of the energy supply by implementing a variety of actions by using the evaluation of these factors as an early warning system. This research aims to provide a multi-criterion decision-making (MCDM) method for assessing the sustainability and security of the electrical supply. The weights of criteria, which indicate their relative relevance in the assessment of the sustainability and security of the energy supply, the MCDM… More >

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