Research Article
Tracing the Evolution of Max-Min Aggregation and Fuzzy Systems in AI: A Bibliometric Review
@ARTICLE{10.4108/eetcasa.9750, author={Nguyen Van Han}, title={Tracing the Evolution of Max-Min Aggregation and Fuzzy Systems in AI: A Bibliometric Review}, journal={EAI Endorsed Transactions on Contex-aware Systems and Applications}, volume={10}, number={1}, publisher={EAI}, journal_a={CASA}, year={2025}, month={7}, keywords={Max-Min Aggregation, Explainable AI, Bibliometric Analysis, Artificial Intelligence, Fuzzy Systems, Neuro-Fuzzy Models}, doi={10.4108/eetcasa.9750} }- Nguyen Van Han
Year: 2025
Tracing the Evolution of Max-Min Aggregation and Fuzzy Systems in AI: A Bibliometric Review
CASA
EAI
DOI: 10.4108/eetcasa.9750
Abstract
This paper presents a bibliometric review of Max-Min aggregation functions and fuzzy systems in artificial intelligence (AI) from 1990 to 2024. Drawing on data from Scopus and analyzed using Bibliometrix and VOSviewer, we map publication trends, key contributors, thematic developments, and emerging research areas. The findings reveal growing interest in interpretable AI, neuro-fuzzy models, and hybrid systems. We highlight the integration of Max-Min aggregation in explainable AI and identify key research gaps. This review provides a structured overview of the field’s evolution and offers guidance for future research directions.
Copyright © 2025 Nguyen Van Han, licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
