The rough set theory is a nonstatistical mathematical approach to address the issues of
vagueness and uncertain knowledge. The rationale of this theory relies on associating a …

The present work proposes new styles of rough sets by using different neighborhoods which
are made from a general binary relation. The proposed approximations represent a …

Approximation space can be said to play a critical role in the accuracy of the set's
approximations. The idea of “approximation space” was introduced by Pawlak in 1982 as a …

The rough set principle was proposed as a methodology to cope with vagueness or
uncertainty of data in the information systems. Day by day, this theory has proven its …

There are many approaches to deal with vagueness and ambiguity including soft sets and
rough sets. Feng et al. initiated the concept of possible hybridization of soft sets and rough …

In this paper, we generalize three types of rough set models based on j-neighborhood space
(ie, type 1 j-neighborhood rough set, type 2 j-neighborhood rough set, and type 3 j …

Decision-making in diagnosing heart failure problems using basic rough sets Page 1 AIMS
Mathematics, 9(8): 21816–21847. DOI: 10.3934/math.20241061 Received: 10 May 2024 …

The generalizations of rough sets based on topological structures have become the hot topic
of rough set theory. In the present article, based on the notion of j-neighborhood space and …

Neighborhood systems are used to approximate graphs as finite topological structures.
Throughout this article, we construct new types of eight neighborhoods for vertices of an …

Covering-based rough sets are important generalizations of the classical rough sets of
Pawlak. In this paper, by means of j-neighborhoods, complementary j-neighborhoods and j …