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 …

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 …

In this work, our target point is to focus on rough approximation operators generated from
infra-topology spaces and examine their features. First, we show how infra-topology spaces …

The theory of rough set is a robust approach to face uncertainty by classifying the data under
study into three main regions. The main principles of this theory are approximation operators …

One of the most popular and important tools to deal with imperfect knowledge is the rough
set theory. It starts from dividing the universe to obtain blocks utilizing an equivalence …

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 …

Our aim of writing this manuscript is to found novel rough-approximation operators inspired
by an abstract structure called “supra-topology”. This approach is more relaxed than …

Rough set theory is a mathematical technique to address the issues of uncertainty and
vagueness in knowledge. It relies mainly on two approximations namely, lower and upper …

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

The current work concentrates on generating different topologies by using the concept of the
ideal. These topologies are used to make more thorough studies on generalized rough set …