Interpretability indices for hierarchical fuzzy systems
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 indic...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
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IEEE
2017
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| Online Access: | https://eprints.nottingham.ac.uk/42290/ |
| _version_ | 1848796454964953088 |
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| author | Razak, T.R. Garibaldi, Jonathan M. Wagner, Christian Pourabdollah, Amir Soria, Daniele |
| author_facet | Razak, T.R. Garibaldi, Jonathan M. Wagner, Christian Pourabdollah, Amir Soria, Daniele |
| author_sort | Razak, T.R. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:48:15Z |
| format | Conference or Workshop Item |
| id | nottingham-42290 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:48:15Z |
| publishDate | 2017 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-422902020-05-04T19:02:00Z https://eprints.nottingham.ac.uk/42290/ Interpretability indices for hierarchical fuzzy systems Razak, T.R. Garibaldi, Jonathan M. Wagner, Christian Pourabdollah, Amir Soria, Daniele 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. IEEE 2017-08-24 Conference or Workshop Item PeerReviewed Razak, T.R., Garibaldi, Jonathan M., Wagner, Christian, Pourabdollah, Amir and Soria, Daniele (2017) Interpretability indices for hierarchical fuzzy systems. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017), 9-12 July 2017, Naples, Italy. http://ieeexplore.ieee.org/document/8015616/ doi:10.1109/FUZZ-IEEE.2017.8015616 doi:10.1109/FUZZ-IEEE.2017.8015616 |
| spellingShingle | Razak, T.R. Garibaldi, Jonathan M. Wagner, Christian Pourabdollah, Amir Soria, Daniele Interpretability indices for hierarchical fuzzy systems |
| title | Interpretability indices for hierarchical fuzzy systems |
| title_full | Interpretability indices for hierarchical fuzzy systems |
| title_fullStr | Interpretability indices for hierarchical fuzzy systems |
| title_full_unstemmed | Interpretability indices for hierarchical fuzzy systems |
| title_short | Interpretability indices for hierarchical fuzzy systems |
| title_sort | interpretability indices for hierarchical fuzzy systems |
| url | https://eprints.nottingham.ac.uk/42290/ https://eprints.nottingham.ac.uk/42290/ https://eprints.nottingham.ac.uk/42290/ |