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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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
IEEE
2016
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| Subjects: | |
| Online Access: | 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 |
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| Summary: | 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. |
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