Conflict Analysis for Pythagorean Fuzzy Information Systems with Group Decision Making

TL;DR

This paper introduces a novel conflict analysis framework for Pythagorean fuzzy information systems, utilizing alliances and Bayesian minimum risk theory to enhance group decision-making under uncertainty.

Contribution

It develops a new conflict analysis method for Pythagorean fuzzy systems and extends it to group decision-making using Bayesian minimum risk theory.

Findings

Defined positive, central, and negative alliances with thresholds

Illustrated alliance construction with examples

Applied Bayesian minimum risk theory to conflict analysis

Abstract

Pythagorean fuzzy sets provide stronger ability than intuitionistic fuzzy sets to model uncertainty information and knowledge, but little effort has been paid to conflict analysis of Pythagorean fuzzy information systems. In this paper, we present three types of positive, central, and negative alliances with different thresholds, and employ examples to illustrate how to construct the positive, central, and negative alliances. Then we study conflict analysis of Pythagorean fuzzy information systems based on Bayesian minimum risk theory. Finally, we investigate group conflict analysis of Pythagorean fuzzy information systems based on Bayesian minimum risk theory.