Interpretable research of fuzzy methods: A literature survey

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Ke Zhang, Tianhao Shao, Yi Sun, Xinyao Xu, Xiaoxiong Zhang, Xiaolei Zhou, Kun Ding, Shan Huang

Published: 2026, Last Modified: 06 Nov 2025Inf. Fusion 2026EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•This paper presents the first systematic review of interpretable fuzzy methods, covering advancements from 2019 to the present.•This paper proposes a novel five-layer tree-like taxonomy based on interpretation type and model structure, categorizing interpretable fuzzy methods into fourteen distinct classes.•This paper systematically analyzes the accuracy-interpretability trade-off in fuzzy systems through empirical evidence from 50+ reviewed studies.•This paper identifies seven key trends, including human cognition simulation and humanmachine interaction.