Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems

Hierarchical Fuzzy Systems (HFSs) have been viewed as a promising option to overcoming a fundamental problem in Fuzzy Logic Systems (FLSs), namely the rule explosion associated with an increase in input variables. In HFSs, the original FLS is decomposed into a number of low-dimensional fuzzy logic s...

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Published in:IEEE International Conference on Fuzzy Systems
Main Author: Razak T.R.; Kamis N.H.; Anuar N.H.; Garibaldi J.M.; Wagner C.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178521198&doi=10.1109%2fFUZZ52849.2023.10309727&partnerID=40&md5=284f611ea9874880da17fd07cf20525b
id 2-s2.0-85178521198
spelling 2-s2.0-85178521198
Razak T.R.; Kamis N.H.; Anuar N.H.; Garibaldi J.M.; Wagner C.
Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
2023
IEEE International Conference on Fuzzy Systems


10.1109/FUZZ52849.2023.10309727
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178521198&doi=10.1109%2fFUZZ52849.2023.10309727&partnerID=40&md5=284f611ea9874880da17fd07cf20525b
Hierarchical Fuzzy Systems (HFSs) have been viewed as a promising option to overcoming a fundamental problem in Fuzzy Logic Systems (FLSs), namely the rule explosion associated with an increase in input variables. In HFSs, the original FLS is decomposed into a number of low-dimensional fuzzy logic subsystems. As a result, rules in HFSs typically have antecedents with fewer variables than rules in FLSs which compute similar function mappings, given that the number of input variables of each subsystem is smaller. Consequently, HFSs tend to limit rule explosion, lowering complexity and enhancing model interpretability. However, developing the HFSs is difficult due to the added issue of designing suitable architecture (i.e., various subsystems, levels, topologies, and subsystem interactions) and rules for each subsystem. In fact, decomposing conventional fuzzy system is a challenging task. The difficulties include: 'How to select the input variable for each subsystem', 'How to improve the meaning of intermediate variable?', 'How to link all the subsystems in HFSs?', and 'How to design the rules for each subsystem?' Hence, this paper presents a method to convert conventional FLSs to hierarchical fuzzy systems using two key steps. This method contributes to the process or guidelines in overcoming the difficulties in the decomposition of FLS to HFS. © 2023 IEEE.
Institute of Electrical and Electronics Engineers Inc.
10987584
English
Conference paper

author Razak T.R.; Kamis N.H.; Anuar N.H.; Garibaldi J.M.; Wagner C.
spellingShingle Razak T.R.; Kamis N.H.; Anuar N.H.; Garibaldi J.M.; Wagner C.
Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
author_facet Razak T.R.; Kamis N.H.; Anuar N.H.; Garibaldi J.M.; Wagner C.
author_sort Razak T.R.; Kamis N.H.; Anuar N.H.; Garibaldi J.M.; Wagner C.
title Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
title_short Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
title_full Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
title_fullStr Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
title_full_unstemmed Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
title_sort Decomposing Conventional Fuzzy Logic Systems to Hierarchical Fuzzy Systems
publishDate 2023
container_title IEEE International Conference on Fuzzy Systems
container_volume
container_issue
doi_str_mv 10.1109/FUZZ52849.2023.10309727
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178521198&doi=10.1109%2fFUZZ52849.2023.10309727&partnerID=40&md5=284f611ea9874880da17fd07cf20525b
description Hierarchical Fuzzy Systems (HFSs) have been viewed as a promising option to overcoming a fundamental problem in Fuzzy Logic Systems (FLSs), namely the rule explosion associated with an increase in input variables. In HFSs, the original FLS is decomposed into a number of low-dimensional fuzzy logic subsystems. As a result, rules in HFSs typically have antecedents with fewer variables than rules in FLSs which compute similar function mappings, given that the number of input variables of each subsystem is smaller. Consequently, HFSs tend to limit rule explosion, lowering complexity and enhancing model interpretability. However, developing the HFSs is difficult due to the added issue of designing suitable architecture (i.e., various subsystems, levels, topologies, and subsystem interactions) and rules for each subsystem. In fact, decomposing conventional fuzzy system is a challenging task. The difficulties include: 'How to select the input variable for each subsystem', 'How to improve the meaning of intermediate variable?', 'How to link all the subsystems in HFSs?', and 'How to design the rules for each subsystem?' Hence, this paper presents a method to convert conventional FLSs to hierarchical fuzzy systems using two key steps. This method contributes to the process or guidelines in overcoming the difficulties in the decomposition of FLS to HFS. © 2023 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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