Weighted fuzzy interpolative reasoning method

Interpolative reasoning method is a reasoning technique, which is designed to deal with reasoning in sparse rule-based systems. This paper proposed a weighted fuzzy interpolative reasoning method by using a like-gravity-centre of fuzzy sets whose shapes are trapezoidal. This method allows the conditions appearing in the antecedent part and the consequence of the rules, the certainty factors of the rules, and the weights of the conditions appearing in the antecedent part of the rules to be represented by trapezoidal fuzzy numbers. We use scale and move rate transformation operation to support such reasoning. The presented method are constructing a new inference rule first by manipulating two given adjacent rules and next by exploiting similarity information to convert the derived inference result into the conclusion.