Worldwide Research Trends in Fuzzy Logic for Computational Intelligence: A Bibliometric and Network Analysis

Worldwide Research Trends in Fuzzy Logic for Computational Intelligence: A Bibliometric and Network Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Worldwide Research Trends in Fuzzy Logic for Computational Intelligence: A Bibliometric and Network Analysis DR. DEBDAS MONDAL This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8490836/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study presents a comprehensive bibliometric and network analysis of global research trends in fuzzy logic for computational intelligence spanning the period 1996–2024. Using publication, citation, co-authorship, and keyword co-occurrence data, the analysis reveals a sustained rise in research output, indicating the field’s maturity and enduring scholarly relevance. High-impact Q1 journals, particularly IEEE Transactions on Fuzzy Systems , Applied Soft Computing, and Information Sciences , emerge as the primary outlets for dissemination, demonstrating the rigorous and high-quality nature of research in the domain. Country-wise mapping highlights China, India, and the United States as leading contributors, supported by strong international collaborative clusters involving globally recognised institutions such as MIT, the Chinese Academy of Sciences, IITs, and Kyushu University. Influential authors, including M. Sugeno, J. Mendel, and H. Wang, show significant contributions to the development of advanced fuzzy methodologies and hybrid intelligence models. Thematic evolution indicates a shift from foundational fuzzy control and inference systems to emerging interdisciplinary applications, particularly in IoT-enabled systems, autonomous robotics, smart healthcare, and optimisation-driven decision support. Overall, the findings underscore fuzzy logic’s dynamic progression and its expanding role in addressing modern technological challenges across diverse sectors. Library Science Fuzzy Logic Computational Intelligence Bibliometric Analysis Scientometrics Co-authorship Networks Research Trends Neuro-Fuzzy Systems IoT Robotics Smart Healthcare Optimisation Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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