A New Monotonicity Index for Fuzzy Rule-based Systems
A search in the literature reveals that mathematical conditions (usually sufficient conditions) for the Fuzzy Inference System (FIS) models to satisfy the monotonicity property have been developed. A monotonicallyordered fuzzy rule base is important to maintain the monotonicity property of an FIS....
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2014
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| Online Access: | http://ir.unimas.my/id/eprint/5182/ http://ir.unimas.my/id/eprint/5182/1/a%20new%20monotonicity%20index%20for%20fuzzy%20rule-based%20systems%20%28abstract%29.pdf |
| _version_ | 1848835601866948608 |
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| author | Lie, Meng Pang Kai, Meng Tay Chee, Peng Lim |
| author_facet | Lie, Meng Pang Kai, Meng Tay Chee, Peng Lim |
| author_sort | Lie, Meng Pang |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | A search in the literature reveals that mathematical conditions (usually sufficient conditions) for the
Fuzzy Inference System (FIS) models to satisfy the
monotonicity property have been developed. A monotonicallyordered fuzzy rule base is important to maintain the monotonicity property of an FIS. However, it may difficult to obtain a monotonically-ordered fuzzy rule base in practice. We have previously introduced the idea of fuzzy rule relabeling to tackle this problem. In this paper, we further propose a monotonicity index for the FIS system, which serves as a metric to indicate the degree of a fuzzy rule base fulfilling the monotonicity property. The index is useful to provide an indication whether a fuzzy rule base should (or should not) be
used in practice, even with fuzzy rule relabeling. To illustrate the idea, the zero-order Sugeno FIS model is exemplified. We add noise as errors into the fuzzy rule base to formulate a set of non-monotone fuzzy rules. As such, the metric also acts as a measure of noise in the fuzzy rule base. The results show that the proposed metric is useful to indicate the degree of a fuzzy
rule base fulfilling the monotonicity property. |
| first_indexed | 2025-11-15T06:10:28Z |
| format | Article |
| id | unimas-5182 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:10:28Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-51822015-03-11T03:45:25Z http://ir.unimas.my/id/eprint/5182/ A New Monotonicity Index for Fuzzy Rule-based Systems Lie, Meng Pang Kai, Meng Tay Chee, Peng Lim TA Engineering (General). Civil engineering (General) A search in the literature reveals that mathematical conditions (usually sufficient conditions) for the Fuzzy Inference System (FIS) models to satisfy the monotonicity property have been developed. A monotonicallyordered fuzzy rule base is important to maintain the monotonicity property of an FIS. However, it may difficult to obtain a monotonically-ordered fuzzy rule base in practice. We have previously introduced the idea of fuzzy rule relabeling to tackle this problem. In this paper, we further propose a monotonicity index for the FIS system, which serves as a metric to indicate the degree of a fuzzy rule base fulfilling the monotonicity property. The index is useful to provide an indication whether a fuzzy rule base should (or should not) be used in practice, even with fuzzy rule relabeling. To illustrate the idea, the zero-order Sugeno FIS model is exemplified. We add noise as errors into the fuzzy rule base to formulate a set of non-monotone fuzzy rules. As such, the metric also acts as a measure of noise in the fuzzy rule base. The results show that the proposed metric is useful to indicate the degree of a fuzzy rule base fulfilling the monotonicity property. IEEE 2014 Article PeerReviewed text en http://ir.unimas.my/id/eprint/5182/1/a%20new%20monotonicity%20index%20for%20fuzzy%20rule-based%20systems%20%28abstract%29.pdf Lie, Meng Pang and Kai, Meng Tay and Chee, Peng Lim (2014) A New Monotonicity Index for Fuzzy Rule-based Systems. 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). |
| spellingShingle | TA Engineering (General). Civil engineering (General) Lie, Meng Pang Kai, Meng Tay Chee, Peng Lim A New Monotonicity Index for Fuzzy Rule-based Systems |
| title | A New Monotonicity Index for Fuzzy Rule-based Systems |
| title_full | A New Monotonicity Index for Fuzzy Rule-based Systems |
| title_fullStr | A New Monotonicity Index for Fuzzy Rule-based Systems |
| title_full_unstemmed | A New Monotonicity Index for Fuzzy Rule-based Systems |
| title_short | A New Monotonicity Index for Fuzzy Rule-based Systems |
| title_sort | new monotonicity index for fuzzy rule-based systems |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://ir.unimas.my/id/eprint/5182/ http://ir.unimas.my/id/eprint/5182/1/a%20new%20monotonicity%20index%20for%20fuzzy%20rule-based%20systems%20%28abstract%29.pdf |