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Fuzzy Rules Reduction Using Rough Set Approach

Yusof, Norazah and Hamdan, Abdul Razak (2003) Fuzzy Rules Reduction Using Rough Set Approach. In: Advanced Technology Congress, 20 - 21 May, 2003, Putrajaya, Kuala Lumpur.

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Abstract

This paper presents the use of Rough Set approach to compute reducts and generate concise fuzzy rules from a fuzzy rule base system of a student model. The purpose of modeling the student is to evaluate the student’s conceptual understanding (i.e. performance level and learning efficiency) in learning C programming language. Based on the Rough Set approach, the fuzzy rule base system that consists of four antecedents and two consequents is transformed into a decision table with four conditional attributes and a single decision attribute. Johnson reducer and Genetic Algorithm reducer are the methods used for computing reducts. Experimental results have shown that Rough Set approach has successfully reduced the fuzzy rules optimally. The number of rules being reduced depends on the refinement and the consistencies of the decision attribute values. After comparing the defuzzified values of the original fuzzy rule base system with the reduced fuzzy rule base system, no obvious degradation of performance occurred. Thus, the reduced fuzzy rule base is said to preserve the same performance as the original fuzzy rule base system.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Rough Set, Fuzzy logic, Reduct computation, Student model, Set Kasar, Logik Kabur, Pengkomputeran reduk, Model pelajar
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:3399
Deposited By: Dr. Norazah Yusof
Deposited On:24 May 2007 08:01
Last Modified:23 Jun 2010 08:33

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