Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System
To maintain the monotonicity property of a fuzzy inference system, a monotonically-ordered and complete set of fuzzy rules is necessary. However, monotonically-ordered fuzzy rules are not always available, e.g. errors in human judgements lead to non-monotone fuzzy rules. The focus of this paper is o...
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my.unimas.ir.121322017-04-12T02:28:02Z http://ir.unimas.my/id/eprint/12132/ Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System Tay, Kai Meng Liew, Meng Pang Chee, Peng Lim QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) To maintain the monotonicity property of a fuzzy inference system, a monotonically-ordered and complete set of fuzzy rules is necessary. However, monotonically-ordered fuzzy rules are not always available, e.g. errors in human judgements lead to non-monotone fuzzy rules. The focus of this paper is on a new monotone fuzzy rule relabeling (MFRR) method that is able to relabel a set of non-monotone fuzzy rules to meet the monotonicity property with reduced computation. Unlike the brute-force approach, which is susceptible to the combinatorial explosion problem, the proposed MFRR method explores within a reduced search space to find the solutions; therefore decreasing the computational requirements. The usefulness of the proposed method in undertaking Failure Mode and Effect Analysis problems is demonstrated using publicly available information. The results indicate that the MFRR method can produce optimal solutions with reduced computational time. IEEE 2016 E-Article PeerReviewed text en http://ir.unimas.my/id/eprint/12132/1/monotone%20fuzzy%20rule%20relabeling%20for%20the%20zero%20%28abstract%29.pdf Tay, Kai Meng and Liew, Meng Pang and Chee, Peng Lim (2016) Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System. IEEE Transactions on Fuzzy Systems, 24 (6). pp. 1455-1463. ISSN 1063-6706 (In Press) http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7429714 10.1109/TFUZZ.2016.2540059 |
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QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) Tay, Kai Meng Liew, Meng Pang Chee, Peng Lim Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System |
description |
To maintain the monotonicity property of a fuzzy inference system, a monotonically-ordered and complete set of fuzzy rules is necessary. However, monotonically-ordered fuzzy rules are not always available, e.g. errors in human judgements lead to non-monotone fuzzy rules. The focus of this paper is on a new monotone fuzzy rule relabeling (MFRR) method that is able to relabel a set of non-monotone fuzzy rules to meet the monotonicity property with reduced computation. Unlike the brute-force approach, which is susceptible to the combinatorial explosion problem, the proposed MFRR method explores within a reduced search space to find the solutions; therefore decreasing the computational requirements. The usefulness of the proposed method in undertaking Failure Mode and Effect Analysis problems is demonstrated using publicly available information. The results indicate that the MFRR method can produce optimal solutions with reduced computational time. |
format |
E-Article |
author |
Tay, Kai Meng Liew, Meng Pang Chee, Peng Lim |
author_facet |
Tay, Kai Meng Liew, Meng Pang Chee, Peng Lim |
author_sort |
Tay, Kai Meng |
title |
Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System |
title_short |
Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System |
title_full |
Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System |
title_fullStr |
Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System |
title_full_unstemmed |
Monotone Fuzzy Rule Relabeling for the Zero-Order TSK Fuzzy Inference System |
title_sort |
monotone fuzzy rule relabeling for the zero-order tsk fuzzy inference system |
publisher |
IEEE |
publishDate |
2016 |
url |
http://ir.unimas.my/id/eprint/12132/1/monotone%20fuzzy%20rule%20relabeling%20for%20the%20zero%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/12132/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7429714 |
_version_ |
1644511348043808768 |
score |
13.250246 |