Adaptive fuzzy interpolative reasoning based on similarity measures of polygonal fuzzy sets and novel move and transformation techniques

Abstract

In this paper, we propose a new adaptive fuzzy interpolative reasoning (AFIR) method based on similarity measures of polygonal fuzzy sets (PFSs) and novel move and transformation techniques for solving contradictory fuzzy interpolative reasoning (FIR) results that occur at FIR components. The proposed AFIR method is applied for dealing with the diarrheal disease prediction problem. The experimental results show that the proposed AFIR method obtains a higher consistency degree between the FIR results compared to the ones obtained by Chen and Adam's AFIR method (2017), Chen and Adam's AFIR method (2018), Chen and Barman's AFIR method (2019), Cheng et al.’s AFIR method (2016), Yang et al.’s AFIR method (2017) and Yang and Shen's AFIR method (2011).