A concise fuzzy rule base to reason student performance based on rough-fuzzy approach
A fuzzy inference system employing fuzzy if then rules able to model the qualitative aspects of human expertise and reasoning processes without employing precise quantitative analyses. This is due to the fact that the problem in acquiring knowledge from human experts is that much of the information...
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| Format: | Book Section |
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IGI global
2012
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| _version_ | 1796859179243143168 |
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| author | Yusof, Norazah Ahmad, Nor Bahiah Othman, Mohd. Shahizan Yeap, Chun Nyen |
| author_facet | Yusof, Norazah Ahmad, Nor Bahiah Othman, Mohd. Shahizan Yeap, Chun Nyen |
| author_sort | Yusof, Norazah |
| collection | ePrints |
| description | A fuzzy inference system employing fuzzy if then rules able to model the qualitative aspects of human expertise and reasoning processes without employing precise quantitative analyses. This is due to the fact that the problem in acquiring knowledge from human experts is that much of the information is uncertain, inconsistent, vague and incomplete (Khoo and Zhai, 2001; Tsaganou et al., 2002; San Pedro and Burstein, 2003; Yang et al., 2005). The drawbacks of FIS are that a lot of trial and error effort need to be taken into account in order to define the best fitted membership functions (Taylan and Karagözoglu, 2009) and no standard methods exist for transforming human knowledge or experience into the rule base (Jang, 1993). |
| first_indexed | 2024-03-05T19:23:21Z |
| format | Book Section |
| id | utm.eprints-47734 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:23:21Z |
| publishDate | 2012 |
| publisher | IGI global |
| record_format | dspace |
| spelling | utm.eprints-477342017-09-19T07:43:49Z http://eprints.utm.my/47734/ A concise fuzzy rule base to reason student performance based on rough-fuzzy approach Yusof, Norazah Ahmad, Nor Bahiah Othman, Mohd. Shahizan Yeap, Chun Nyen QA Mathematics A fuzzy inference system employing fuzzy if then rules able to model the qualitative aspects of human expertise and reasoning processes without employing precise quantitative analyses. This is due to the fact that the problem in acquiring knowledge from human experts is that much of the information is uncertain, inconsistent, vague and incomplete (Khoo and Zhai, 2001; Tsaganou et al., 2002; San Pedro and Burstein, 2003; Yang et al., 2005). The drawbacks of FIS are that a lot of trial and error effort need to be taken into account in order to define the best fitted membership functions (Taylan and Karagözoglu, 2009) and no standard methods exist for transforming human knowledge or experience into the rule base (Jang, 1993). IGI global 2012 Book Section PeerReviewed Yusof, Norazah and Ahmad, Nor Bahiah and Othman, Mohd. Shahizan and Yeap, Chun Nyen (2012) A concise fuzzy rule base to reason student performance based on rough-fuzzy approach. In: Fuzzy Inference System - Theory and Applications. IGI global, pp. 324-342. ISBN 978-1-4666-1993-7 https://www.researchgate.net/publication/300804865_A_Concise_Fuzzy_Rule_Base_to_Reason_Student_Performance_Based_on_Rough-Fuzzy_Approach |
| spellingShingle | QA Mathematics Yusof, Norazah Ahmad, Nor Bahiah Othman, Mohd. Shahizan Yeap, Chun Nyen A concise fuzzy rule base to reason student performance based on rough-fuzzy approach |
| title | A concise fuzzy rule base to reason student performance based on rough-fuzzy approach |
| title_full | A concise fuzzy rule base to reason student performance based on rough-fuzzy approach |
| title_fullStr | A concise fuzzy rule base to reason student performance based on rough-fuzzy approach |
| title_full_unstemmed | A concise fuzzy rule base to reason student performance based on rough-fuzzy approach |
| title_short | A concise fuzzy rule base to reason student performance based on rough-fuzzy approach |
| title_sort | concise fuzzy rule base to reason student performance based on rough fuzzy approach |
| topic | QA Mathematics |
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