A grade assignment and IFS translation approach based on intensive region searching

Intuitionistic Fuzzy Set (IFS) is considered as a nature solution for information fusion. How to transform the information with non-uniform distribution into IFS? In this paper, the authors proposed an approach to deal with this challenge. First, the intensive region (IR) of non-uniform distribution data is searched. Second, the evaluation grades are assigned to IR and other regions. IR is assigned to more grades, because of the higher data rate in it. Finally, the non-uniform data is translated into IFS based on the suitable grades assignment. The experiment is conducted to study the effectiveness and advantage of this approach.