In this manuscript, we first generate topological structures by subset neighborhoods and
ideals and apply to establish some generalized rough-set models. Then, we present other …

This article aims to define four new kinds of rough set models based on cardinality
neighborhoods and two ideals. The significance of these methods lies in their foundation on …

The idea of nano-topology was originally proposed a decade ago by Thivagar. Since then, a
lot of research has been done on the generalizations of the basic notions of nano-topology …

Rough set theory serves as an effective method for managing complicated real-world data.
Through rough approximation operators, it discerns both confirmed and possible data …

This article introduces novel definitions for generalized rough-set models, that using the
concepts of initial neighborhoods and ideals. A comprehensive examination of the …

In practical life, researchers aim to appropriately frame societal problems and challenges to
address and find effective solutions. One efficient method for managing complex real-world …

Rough set theory is an advanced uncertainty tool that is capable of processing sophisticated
real-world data satisfactorily. Rough approximation operators are used to determine the …

This study focuses on defining separation axioms for sets without an inherent topological
structure. By utilizing a map** to relate such sets to a topological space, we first define a …

This article highlights the concept of generalized π-weak closed sets (briefly, gπ (w)-closed)
in weak structures, that possess a lot of applications in information systems. We study their …

Rough set theory is an advanced uncertainty tool that is capable of processing sophisticated
real-world data satisfactorily. Rough approximation operators are used to determine the …