This paper reviews and compares constructive and algebraic approaches in the study of
rough sets. In the constructive approach, one starts from a binary relation and defines a pair …

Semantics-preserving dimensionality reduction refers to the problem of selecting those input
features that are most predictive of a given outcome; a problem encountered in many areas …

It is not widely acknowledged that none of existing fuzzy β-neighborhood operators satisfies
the reflexivity when β≠ 1. To overcome this shortcoming, four types of fuzzy β-neighborhood …

Theories of fuzzy sets and rough sets are powerful mathematical tools for modelling various
types of uncertainty. Dubois and Prade investigated the problem of combining fuzzy sets …

Molodtsov introduced the concept of soft set theory, which can be used as a generic
mathematical tool for dealing with uncertainty. In this paper we introduce the basic …

The original rough set approach proved to be very useful in dealing with inconsistency
problems following from information granulation. It operates on a data table composed of a …

This work improves the theoretical basis of N-soft sets and insists on their practical
applications in a multi-agent context. N-soft sets characterize the alternatives in terms of …

There has been great interest in developing methodologies that are capable of dealing with
imprecision and uncertainty. The large amount of research currently being carried out in …

At present, there is no unified method for solving multiattribute decision-making problems. In
this paper, we propose two methods that benefit from some novel fuzzy rough set models …

Due to the explosive growth of electronically stored information, automatic methods must be
developed to aid users in maintaining and using this abundance of information effectively. In …