Fuzzy Data Analytics: Current Trends and Future Perspectives

Dear Colleagues,

Fuzzy data analytics has become a foundational component in modelling, interpreting and managing complex, uncertain and imprecise information in modern intelligent systems. With the rapid expansion of data-centric technologies—including machine learning, IoT sensing, cyber–physical systems and autonomous decision environments—traditional crisp models are often insufficient for capturing vagueness, ambiguity and incomplete knowledge. Fuzzy set theory and its contemporary extensions offer powerful mechanisms for representing and analysing such uncertainty.

In this Special Issue, we are particularly interested in new theories, algorithms and applications that advance the field of fuzzy data analytics, as well as forward-looking perspectives that identify open challenges and emerging research opportunities. We welcome interdisciplinary contributions that explore the integration of fuzzy systems with artificial intelligence, optimisation, machine learning and real-world decision-support environments.

Topics of interest include, but are not limited to:

• Advanced fuzzy set models: hesitant, intuitionistic, probabilistic, type-2 and higher-order fuzzy representations
• Fuzzy similarity, entropy and knowledge measures for data-driven inference
• Integration of fuzzy logic with machine learning, deep learning and explainable AI
• Granular computing and fuzzy information processing in intelligent systems
• Fuzzy multi-criteria decision making (MCDM) and decision-support frameworks
• Fuzzy analytics for big data, IoT, sensor networks and uncertainty-aware environments
• Applications in environmental modelling, wildfire risk assessment, transportation, health, finance and socio-technical systems
• Future trends and emerging research directions in fuzzy data analytics and computational intelligence

We invite high-quality research articles, reviews, methodological developments and application-oriented studies that contribute to the evolving landscape of fuzzy data analytics.

Dr. Bahram Farhadinia
Dr. Ashkan Hafezalkotob
Guest Editors

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