Weighted Mamdani-type Fuzzy Inference System Based on Relative Ideal Preference System

Daud Mohamad, Fatin Liyana Mukhtar


This paper presents a new method of determining weight of the fuzzy IF-THEN rules in a Fuzzy Inference System based on human intuition or expert judgment, known as the Relative Ideal Preference Scheme (RIPS). In the proposed scheme, an ideal preference rule is chosen from the given set of available fuzzy IF-THEN rules in the system which will be set with weight 1. The threshold weight and the interval between rule's weight are calculated prior to the computation of the weight of other rules. Rules are rearranged based on their level differences with respect to the ideal preferred rule. Finally, the weight of each rule is determined using the calculated threshold and interval between weights. An illustration of its implementation in a fuzzy inference system is presented with a numerical example. The proposed scheme has an advantage where the weights of the rules are determined systematically and simple.



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