Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions
In our previous investigations, two Similarity Reasoning (SR)-based frameworks for tackling real-world problems have been proposed. In both frameworks, SR is used to deduce unknown fuzzy rules based on similarity of the given and unknown fuzzy rules for building a Fuzzy Inference System (FIS). In t...
| Main Authors: | , , , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
IEEE
2014
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/5192/ http://ir.unimas.my/id/eprint/5192/1/building%20fuzzy%20inference%20sytstems%20with%20similarity%20reasoning%20%28abstract%29.pdf |
| _version_ | 1848835605205614592 |
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| author | Tze, Ling Jee Kok, Chin Chai Kai, Meng Tay Chee, Peng Lim |
| author_facet | Tze, Ling Jee Kok, Chin Chai Kai, Meng Tay Chee, Peng Lim |
| author_sort | Tze, Ling Jee |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | In our previous investigations, two Similarity Reasoning (SR)-based frameworks for tackling real-world problems have been proposed. In both frameworks, SR is used
to deduce unknown fuzzy rules based on similarity of the given and unknown fuzzy rules for building a Fuzzy Inference System (FIS). In this paper, we further extend our previous findings by developing (1) a multi-objective evolutionary model for fuzzy rule selection; and (2) an evidential function to facilitate the use of both frameworks. The Non-Dominated Sorting Genetic Algorithms-II (NSGA-II) is adopted for fuzzy rule selection, in
accordance with the Pareto optimal criterion. Besides that, two new evidential functions are developed, whereby given fuzzy rules are considered as evidence. Simulated and benchmark examples are included to demonstrate the applicability of these suggestions. Positive results were obtained. |
| first_indexed | 2025-11-15T06:10:31Z |
| format | Proceeding |
| id | unimas-5192 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:10:31Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-51922015-03-11T04:28:49Z http://ir.unimas.my/id/eprint/5192/ Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions Tze, Ling Jee Kok, Chin Chai Kai, Meng Tay Chee, Peng Lim T Technology (General) TA Engineering (General). Civil engineering (General) In our previous investigations, two Similarity Reasoning (SR)-based frameworks for tackling real-world problems have been proposed. In both frameworks, SR is used to deduce unknown fuzzy rules based on similarity of the given and unknown fuzzy rules for building a Fuzzy Inference System (FIS). In this paper, we further extend our previous findings by developing (1) a multi-objective evolutionary model for fuzzy rule selection; and (2) an evidential function to facilitate the use of both frameworks. The Non-Dominated Sorting Genetic Algorithms-II (NSGA-II) is adopted for fuzzy rule selection, in accordance with the Pareto optimal criterion. Besides that, two new evidential functions are developed, whereby given fuzzy rules are considered as evidence. Simulated and benchmark examples are included to demonstrate the applicability of these suggestions. Positive results were obtained. IEEE 2014 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/5192/1/building%20fuzzy%20inference%20sytstems%20with%20similarity%20reasoning%20%28abstract%29.pdf Tze, Ling Jee and Kok, Chin Chai and Kai, Meng Tay and Chee, Peng Lim (2014) Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions. In: 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) Tze, Ling Jee Kok, Chin Chai Kai, Meng Tay Chee, Peng Lim Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions |
| title | Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions |
| title_full | Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions |
| title_fullStr | Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions |
| title_full_unstemmed | Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions |
| title_short | Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions |
| title_sort | building fuzzy inference systems with similarity reasoning: nsga ii-based fuzzy rule selection and evidential functions |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://ir.unimas.my/id/eprint/5192/ http://ir.unimas.my/id/eprint/5192/1/building%20fuzzy%20inference%20sytstems%20with%20similarity%20reasoning%20%28abstract%29.pdf |