Weighted fuzzy interpolated reasoning based on ranking values of polygonal fuzzy sets and new scale and move transformation techniques

In this paper, we propose a new transformation-based weighted fuzzy interpolative reasoning (FIR) method based on ranking values of polygonal fuzzy sets (PFSs) and the proposed new scale and move transformation techniques. The proposed weighted FIR method gets more reasonable FIR results than the ones of the existing methods, where the weight of each antecedent variable and the weight of each fuzzy rule are generated automatically. Moreover, the proposed new scale and move transformation techniques can deal with FIR using singleton fuzzy sets and PFSs. We also apply the proposed weighted FIR method to predict the diarrheal disease rates in remote villages. The proposed weighted FIR method provides us with a very useful way for weighted FIR in sparse fuzzy rule-based systems.