A New Method to Achieve Fuzzy Set Transformation in Fuzzy Logic System

The core of fuzzy logic system is fuzzy inference machine, which realizes the transformation of fuzzy set from universe of discourse U to universe of discourse V. The fuzzy set transformation is membership transformation. However, there is redundancy in the existing algorithms of membership transformation. In order to construct a membership transformation method in which there is not interfering by redundant data, this paper excavates the information of the object classification that hides in index membership to define the divisional right, this data excavation method is based on entropy; Use distinguishable weight as a filter to delete redundant index membership that are useless for classification, and extract effective value in index membership that is useful for classification; Then transform effective value to comparable value and generate comparable sum; At last define object membership by comparable sum. Based on this, a new method to achieve transformation of fuzzy set can be realized without the interference of redundant data, and the following case can illustrate the algorithm application.