Some Topological Approaches for Generalized Rough Sets and Their Decision-Making Applications

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 efficiency in handling and modeling many real-life problems. To contribute to this area, we present new topological approaches as a generalization of Pawlak's theory by using j-adhesion neighborhoods and elucidate the relationship between them and some other types of approximations with the aid of examples. Topologically, we give another generalized rough approximation using near open sets. Also, we generate generalized approximations created from the topological models of j-adhesion approximations. Eventually, we compare the approaches given herein with previous ones to obtain a more affirmative solution for decision-making problems.

Automated summary

The rough set principle is an efficient method for dealing with the uncertainty of data in information systems. This paper introduces new topological approaches as a generalization of Pawlak's theory, elucidating the relationships between different types of approximations through examples. By comparing these approaches with previous ones, a more affirmative solution for decision-making problems can be obtained.