Adaptive fuzzy interpolation based on general representative values of polygonal fuzzy sets and the shift and modification techniques

Adaptive fuzzy interpolative reasoning (AFIR) can overcome the limitation of the conventional fuzzy interpolation techniques because it can find and solve the contradictions of the fuzzy interpolative reasoning (FIR) results in order to ensure that the derived FIR results are consistent. In this paper, we propose a new AFIR method to solve the inconsistencies occurring after the FIR process. The proposed AFIR method is based on the general representative values of polygonal fuzzy sets and the proposed shift and modification techniques. The proposed AFIR method includes a new contradictions solving method to get a higher similarity degree between the AFIR results. In order to demonstrate the higher consistency of the AFIR results obtained by the proposed AFIR method, we apply the proposed AFIR method to deal with the diarrheal disease prediction problem. The experimental results show that the proposed AFIR method outperforms Yang and Shen's AFIR method (2011) and Cheng et al.'s AFIR method (2016) in terms of the degree of similarity between the AFIR results.