Rough set theory is a key approach to model and apprehend the situations involving
uncertainty without additional information and suppositions. Complex fuzzy sets are useful in …

The key strategy of the three-way decisions theory is to consider a decision-making problem
as a ternary classification one (ie acceptance, rejection and non-commitment). Recently, this …

A fuzzy rough set is an important rough set model used for feature selection. It uses the fuzzy
rough dependency as a criterion for feature selection. However, this model can merely …

As a natural extension of three-way decisions with incomplete information, this paper
provides a novel three-way decision model based on incomplete information system. First …

Neighborhood rough sets are widely used as an effective tool to deal with numerical data.
However, most of the existing neighborhood granulation models cannot well describe the …

In this paper, we investigate the relationships among rough sets, soft sets and hemirings.
The concept of soft rough hemirings is introduced, which is an extended notion of a rough …

Recently, by combining rough set theory with granular computing, pessimistic and optimistic
multigranulation rough sets have been proposed to derive “AND” and “OR” decision rules …

There exist several approaches to rough set approximations in a multigranulation space,
namely, a family of equivalence relations. In this paper, we propose a unified framework to …

Fuzzy sets and fuzzy rough sets are widely applied in data analysis, data mining, and
decision-making. So far, the common method is to use rough approximate operators to …

This paper introduces the notion of Z-soft rough fuzzy sets of hemirings, which is an
extended notion of soft rough sets and rough fuzzy sets. It is pointed out that this novel …