Exploring Diverse Rough Neighborhoods Through Graphical Analysis

The world’s knowledge is believed to double every ten months, and this vast pool of information often contains incomplete data, imperfections, uncertainties, and vague elements. Converting such data into meaningful patterns is a crucial task for data analysts. In this research, we have explored various mathematical models for this purpose. Among these models, we focused on Pawlak’s Rough Set model applied through Rough Graphs. Our work presents a novel form of Rough Neighborhood System, as demonstrated in this paper

New Rough Set Approximation Spaces

Rough set theory was introduced by Pawlak in 1982 to handle imprecision, vagueness, and uncertainty in data analysis. Our aim is to generalize rough set theory by introducing concepts of -lower and -upper approximations which depends on the concept of -sets. Also, we study some of their basic properties