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Interpretability indices for hierarchical fuzzy systems

Razak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A., Soria, D. (2017) Interpretability indices for hierarchical fuzzy systems. In: IEEE International Conference on Fuzzy Systems. . Institute of Electrical and Electronics Engineers Inc. (doi:10.1109/FUZZ-IEEE.2017.8015616) (KAR id:98875)


Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve interpretability of fuzzy logic systems (FLSs). In recent years, a variety of indices have been proposed to measure the interpretability of FLSs such as the Nauck index and Fuzzy index. However, interpretability indices associated with HFSs have not so far been discussed. The structure of HFSs, with multiple layers, subsystems, and varied topologies, is the main challenge in constructing interpretability indices for HFSs. Thus, the comparison of interpretability between FLSs and HFSs - even at the index level - is still subject to open discussion. This paper begins to address these challenges by introducing extensions to the FLS Nauck and Fuzzy interpretability indices for HFSs. Using the proposed indices, we explore the concept of interpretability in relation to the different structures in FLSs and HFSs. Initial experiments on benchmark datasets show that based on the proposed indices, HFSs with equivalent function to FLSs produce higher indices, i.e. are more interpretable than their corresponding FLSs. © 2017 IEEE.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/FUZZ-IEEE.2017.8015616
Additional information: cited By 25
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: Engineering and Physical Sciences Research Council (
Depositing User: Daniel Soria
Date Deposited: 07 Dec 2022 16:24 UTC
Last Modified: 04 Mar 2024 17:28 UTC
Resource URI: (The current URI for this page, for reference purposes)

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