A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems

A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of a Fuzzy Inference System (FIS). In this paper, a new monotone fuzzy rule relabeling technique to relabel a non-monotone fuzzy rule base provided by domain experts is proposed. Even though t...

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Main Authors:	Tay, Kai Meng, Liew, Meng Pang, Tze, Ling Jee
Format:	Article
Language:	English
Published:	IEEE 2013
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://ir.unimas.my/id/eprint/16639/ http://ir.unimas.my/id/eprint/16639/1/A%20New%20Framework%20With%20Similarity%20Reasoning%20%28abstract%29.pdf

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author	Tay, Kai Meng Liew, Meng Pang Tze, Ling Jee
author_facet	Tay, Kai Meng Liew, Meng Pang Tze, Ling Jee
author_sort	Tay, Kai Meng
building	UNIMAS Institutional Repository
collection	Online Access
description	A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of a Fuzzy Inference System (FIS). In this paper, a new monotone fuzzy rule relabeling technique to relabel a non-monotone fuzzy rule base provided by domain experts is proposed. Even though the Genetic Algorithm (GA)-based monotone fuzzy rule relabeling technique has been investigated in our previous work [7], the optimality of the approach could not be guaranteed. The new fuzzy rule relabeling technique adopts a simple brute force search, and it can produce an optimal result. We also formulate a new two-stage framework that encompasses a GA-based rule selection scheme, the optimization based-Similarity Reasoning (SR) scheme, and the proposed monotone fuzzy rule relabeling technique for preserving the monotonicity property of the FIS model. Applicability of the two-stage framework to a real world problem, i.e., failure mode and effect analysis, is further demonstrated. The results clearly demonstrate the usefulness of the proposed framework.
first_indexed	2025-11-15T06:50:14Z
format	Article
id	unimas-16639
institution	Universiti Malaysia Sarawak
institution_category	Local University
language	English
last_indexed	2025-11-15T06:50:14Z
publishDate	2013
publisher	IEEE
recordtype	eprints
repository_type	Digital Repository
spelling	unimas-166392017-06-14T06:03:11Z http://ir.unimas.my/id/eprint/16639/ A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems Tay, Kai Meng Liew, Meng Pang Tze, Ling Jee TA Engineering (General). Civil engineering (General) A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of a Fuzzy Inference System (FIS). In this paper, a new monotone fuzzy rule relabeling technique to relabel a non-monotone fuzzy rule base provided by domain experts is proposed. Even though the Genetic Algorithm (GA)-based monotone fuzzy rule relabeling technique has been investigated in our previous work [7], the optimality of the approach could not be guaranteed. The new fuzzy rule relabeling technique adopts a simple brute force search, and it can produce an optimal result. We also formulate a new two-stage framework that encompasses a GA-based rule selection scheme, the optimization based-Similarity Reasoning (SR) scheme, and the proposed monotone fuzzy rule relabeling technique for preserving the monotonicity property of the FIS model. Applicability of the two-stage framework to a real world problem, i.e., failure mode and effect analysis, is further demonstrated. The results clearly demonstrate the usefulness of the proposed framework. IEEE 2013 Article PeerReviewed text en http://ir.unimas.my/id/eprint/16639/1/A%20New%20Framework%20With%20Similarity%20Reasoning%20%28abstract%29.pdf Tay, Kai Meng and Liew, Meng Pang and Tze, Ling Jee (2013) A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems. IEEE International Conference on Fuzzy Systems (FUZZ), 2013. ISSN 1098-7584 http://ieeexplore.ieee.org/document/6622455/ DOI: 10.1109/FUZZ-IEEE.2013.6622455
spellingShingle	TA Engineering (General). Civil engineering (General) Tay, Kai Meng Liew, Meng Pang Tze, Ling Jee A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
title	A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
title_full	A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
title_fullStr	A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
title_full_unstemmed	A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
title_short	A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems
title_sort	new framework with similarity reasoning and monotone fuzzy rule relabeling for fuzzy inference systems
topic	TA Engineering (General). Civil engineering (General)
url	http://ir.unimas.my/id/eprint/16639/ http://ir.unimas.my/id/eprint/16639/ http://ir.unimas.my/id/eprint/16639/ http://ir.unimas.my/id/eprint/16639/1/A%20New%20Framework%20With%20Similarity%20Reasoning%20%28abstract%29.pdf

A New Framework With Similarity Reasoning and Monotone Fuzzy Rule Relabeling for Fuzzy Inference Systems

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