Novel Parameterized Utility Function on Dual Hesitant Fuzzy Rough Sets and Its Application in Pattern Recognition

Abstract

Based on comparative studies on correlation coefficient theory and utility theory, a series of rules that utility functions on dual hesitant fuzzy rough sets (DHFRSs) should satisfy, and a kind of novel utility function on DHFRSs are proposed. The characteristic of the introduced utility function is a parameter, which is determined by decision-makers according to their experiences. By using the proposed utility function on DHFRSs, a novel dual hesitant fuzzy rough pattern recognition method is also proposed. Furthermore, this study also points out that the classical dual tool is suitable to cope with dynamic data in exploratory data analysis situations, while the newly proposed one is suitable to cope with static data in confirmatory data analysis situations. Finally, a medical diagnosis and a traffic engineering example are introduced to reveal the effectiveness of the newly proposed utility functions on DHFRSs.

A Literature Review of Dual Hesitant Fuzzy Sets / Uma Revisão Da Literatura Sobre Conjuntos Dual Hesitant Fuzzy

“…Medical applications: identification of diseases; evaluation of hospital risks; evaluation of blood donation. Liang et al 2017;Zhang et al 2015;Xu et al 2019;Wu et al, 2019;Wang et al 2013;Arora e Garg 2018;Farhadinia 2014 Qu et al 2018;Maity et al 2019;Zhang 2015;Zhang 2016;Chen et al 2018;Lu et al 2016;Zhang et al 2014;Qu et al 2017;Chen et al 2014.…”