A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems
In this paper, a new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems (FISs) is proposed. The framework encompasses an optimization-based Similarity Reasoning (SR) scheme and a new monotone fuzzy rule relabeling technique. A complete and monotonically-ordere...
| Main Authors: | , , , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
2013
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| Online Access: | http://ir.unimas.my/id/eprint/15837/ http://ir.unimas.my/id/eprint/15837/1/A%20new%20online%20updating%20framework%20for%20constructing%20monotonicity-preserving%20Fuzzy%20Inference%20Systems%20%28abstrak%29.pdf |
| _version_ | 1848837936273948672 |
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| author | Kai, Meng Tay Tze, Ling Jee Lie, Meng Pang Chee, Peng Lim |
| author_facet | Kai, Meng Tay Tze, Ling Jee Lie, Meng Pang Chee, Peng Lim |
| author_sort | Kai, Meng Tay |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | In this paper, a new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems (FISs) is proposed. The framework encompasses an optimization-based Similarity Reasoning (SR) scheme and a new monotone fuzzy rule relabeling technique. A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of an FIS model. The proposed framework attempts to allow a monotonicity-preserving FIS model to be constructed when the fuzzy rules are incomplete and not monotonically-ordered. An online feature is introduced to allow the FIS model to be updated from time to time. We further investigate three useful measures, i.e., the belief, plausibility, and evidential mass measures, which are inspired from the Dempster-Shafer theory of evidence, to analyze the proposed framework and to give an insight for the inferred outcomes from the FIS model |
| first_indexed | 2025-11-15T06:47:34Z |
| format | Proceeding |
| id | unimas-15837 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:47:34Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-158372017-05-02T02:47:34Z http://ir.unimas.my/id/eprint/15837/ A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems Kai, Meng Tay Tze, Ling Jee Lie, Meng Pang Chee, Peng Lim QA Mathematics QA76 Computer software In this paper, a new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems (FISs) is proposed. The framework encompasses an optimization-based Similarity Reasoning (SR) scheme and a new monotone fuzzy rule relabeling technique. A complete and monotonically-ordered fuzzy rule base is necessary to maintain the monotonicity property of an FIS model. The proposed framework attempts to allow a monotonicity-preserving FIS model to be constructed when the fuzzy rules are incomplete and not monotonically-ordered. An online feature is introduced to allow the FIS model to be updated from time to time. We further investigate three useful measures, i.e., the belief, plausibility, and evidential mass measures, which are inspired from the Dempster-Shafer theory of evidence, to analyze the proposed framework and to give an insight for the inferred outcomes from the FIS model 2013 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/15837/1/A%20new%20online%20updating%20framework%20for%20constructing%20monotonicity-preserving%20Fuzzy%20Inference%20Systems%20%28abstrak%29.pdf Kai, Meng Tay and Tze, Ling Jee and Lie, Meng Pang and Chee, Peng Lim (2013) A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems. In: 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013;, 7 July 2013 through 10 July 2013;, Hyderabad; India. http://ieeexplore.ieee.org/document/6622522/ |
| spellingShingle | QA Mathematics QA76 Computer software Kai, Meng Tay Tze, Ling Jee Lie, Meng Pang Chee, Peng Lim A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems |
| title | A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems |
| title_full | A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems |
| title_fullStr | A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems |
| title_full_unstemmed | A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems |
| title_short | A new online updating framework for constructing monotonicity-preserving Fuzzy Inference Systems |
| title_sort | new online updating framework for constructing monotonicity-preserving fuzzy inference systems |
| topic | QA Mathematics QA76 Computer software |
| url | http://ir.unimas.my/id/eprint/15837/ http://ir.unimas.my/id/eprint/15837/ http://ir.unimas.my/id/eprint/15837/1/A%20new%20online%20updating%20framework%20for%20constructing%20monotonicity-preserving%20Fuzzy%20Inference%20Systems%20%28abstrak%29.pdf |