Economic Decision-Making Using Rough Topological Structures

This paper suggests new approximations that are inspired by topological structures. The primary goal of this work is to define four neighborhoods resulting from a binary relation. Thus, we have distinct techniques for approximating rough sets. suggested approaches represent generalizations the previous works. characteristics and connections these investigated. For sake application, provide some useful examples compare our those in published literature. merit current technique obtain more accurate decision problems which cases appropriate frame describe them; instance, machine learning (ML, short) applications finance, etc. To demonstrate fact, an economic application proposed. We employ proposed defining decisions identify growth countries. An algorithm decision-making tested on fictitious data methods with approaches.