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...
Published in: | 2024 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ-IEEE 2024 |
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Main Authors: | , , , |
Format: | Proceedings Paper |
Language: | English |
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IEEE
2024
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Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001293753100095 |
author |
Razak Tajul Rosli; Garibaldi Jonathan M.; Wagner Christian |
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Razak Tajul Rosli; Garibaldi Jonathan M.; Wagner Christian A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems Computer Science; Mathematics |
author_facet |
Razak Tajul Rosli; Garibaldi Jonathan M.; Wagner Christian |
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Razak |
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Razak, Tajul Rosli; Garibaldi, Jonathan M.; Wagner, Christian A Comprehensive Guideline to Design Interpretable Hierarchical Fuzzy Systems 2024 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ-IEEE 2024 English Proceedings Paper 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. IEEE 1544-5615 2024 10.1109/FUZZ-IEEE60900.2024.10612113 Computer Science; Mathematics WOS:001293753100095 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001293753100095 |
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 |
container_title |
2024 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, FUZZ-IEEE 2024 |
language |
English |
format |
Proceedings Paper |
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. |
publisher |
IEEE |
issn |
1544-5615 |
publishDate |
2024 |
container_volume |
|
container_issue |
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doi_str_mv |
10.1109/FUZZ-IEEE60900.2024.10612113 |
topic |
Computer Science; Mathematics |
topic_facet |
Computer Science; Mathematics |
accesstype |
|
id |
WOS:001293753100095 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001293753100095 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1814778544936452096 |