A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems

Hierarchical fuzzy systems (HFSs) are claimed to be an excellent approach to reducing the number of rules in Fuzzy logic systems (FLSs). Further, HFSs have also been shown to have the potential to reduce complexity and improve interpretability for FLSs. However, designing an interpretable HFS is a c...

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Bibliographic Details
Published in:IEEE International Conference on Fuzzy Systems
Main Author: Razak T.R.; Garibaldi J.M.; Wagner C.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201543604&doi=10.1109%2fFUZZ-IEEE60900.2024.10612113&partnerID=40&md5=b09437687d7eba701ec38b59bb6d4b22
id 2-s2.0-85201543604
spelling 2-s2.0-85201543604
Razak T.R.; Garibaldi J.M.; Wagner C.
A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
2024
IEEE International Conference on Fuzzy Systems


10.1109/FUZZ-IEEE60900.2024.10612113
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201543604&doi=10.1109%2fFUZZ-IEEE60900.2024.10612113&partnerID=40&md5=b09437687d7eba701ec38b59bb6d4b22
Hierarchical fuzzy systems (HFSs) are claimed to be an excellent approach to reducing the number of rules in Fuzzy logic systems (FLSs). Further, HFSs have also been shown to have the potential to reduce complexity and improve interpretability for FLSs. However, designing an interpretable HFS is a challenging task. This is due to the HFSs' structures, which have multiple subsystems, layers and topologies. This paper put forward an approach to present a design guidelines framework to build interpretable HFSs. The framework consists of five key guidelines for interpretable HFSs. It is demonstrated using a real-world example to design interpretable HFS for the Iris classification problem. This study contributes to providing insight into a pathway for designing interpretable HFSs, as can be used in practice. © 2024 IEEE.
Institute of Electrical and Electronics Engineers Inc.
10987584
English
Conference paper

author Razak T.R.; Garibaldi J.M.; Wagner C.
spellingShingle Razak T.R.; Garibaldi J.M.; Wagner C.
A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
author_facet Razak T.R.; Garibaldi J.M.; Wagner C.
author_sort Razak T.R.; Garibaldi J.M.; Wagner C.
title A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
title_short A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
title_full A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
title_fullStr A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
title_full_unstemmed A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
title_sort A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems
publishDate 2024
container_title IEEE International Conference on Fuzzy Systems
container_volume
container_issue
doi_str_mv 10.1109/FUZZ-IEEE60900.2024.10612113
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201543604&doi=10.1109%2fFUZZ-IEEE60900.2024.10612113&partnerID=40&md5=b09437687d7eba701ec38b59bb6d4b22
description Hierarchical fuzzy systems (HFSs) are claimed to be an excellent approach to reducing the number of rules in Fuzzy logic systems (FLSs). Further, HFSs have also been shown to have the potential to reduce complexity and improve interpretability for FLSs. However, designing an interpretable HFS is a challenging task. This is due to the HFSs' structures, which have multiple subsystems, layers and topologies. This paper put forward an approach to present a design guidelines framework to build interpretable HFSs. The framework consists of five key guidelines for interpretable HFSs. It is demonstrated using a real-world example to design interpretable HFS for the Iris classification problem. This study contributes to providing insight into a pathway for designing interpretable HFSs, as can be used in practice. © 2024 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn 10987584
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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