Circular Spherical Fuzzy Sugeno Weber Aggregation Operators: A Novel Uncertain Approach for Adaption a Programming Language for Social Media Platform

Abstract

This study's major purpose is to highlight circular spherical fuzzy sets, that happens to be a prolongation of spherical fuzzy sets. The primary purpose of this research is to demonstrate the basic operations and theorems of circular spherical fuzzy structures (C-SFS), which give an effective way for dealing with data ambiguity. Aggregation operators (AOs) play a significant role in decision-making, particularly in situations where conflicting interests need to be taken into account. The Sugeno-Weber (SW) t-conorm and t-norm are employed in the C-SFS operating rules. The study describes in detail the fundamental operating criteria for C-SFS utilizing SW t-norms and t-conorms, as well as their crucial features. Furthermore, this research presents and fully investigates two novel operators, C-SFS Sugeno Weber weighted averaging (C-SFSWWA) and C-SFS Sugeno-Weber weighted geometric (C-SFSWWG), as well as their distinct applications and desired properties. A novel approach based on the C-SFSWWA and C-SFSWWG operators is suggested to address multiple attribute decision-making (MADM) problems utilizing C-SF information. A numerical example shows how this approach may be used to adapt a programming language for social media platform analytics, followed by a comparison study to highlight its advantages. The advised approach is successful, according to an investigation of authenticity and a comparison study. In reality, the recommended aggregation operators and decision-making approach are quite useful for decision analysis.