A generalization of the original idea of rough sets and variable precision rough sets is
introduced. This generalization is based on the concept of absolute and relative rough …

A generalization of the original definition of rough sets and variable precision rough sets is
introduced. This generalization is based on the concept of absolute and relative rough …

A generalization of the original idea of rough sets as introduced by Pawlak is presented. The
generalization, called the Variable Precision Rough Sets Model with Asymmetric Bounds, is …

The original Rough Set model is concerned primarily with algebraic properties of
approximately defined sets. The Variable Precision Rough Set (VPRS) model extends the …

We consider new definitions of Variable Consistency Rough Set Approaches that employ
monotonic measures of membership to the approximated set. The monotonicity is …

The paper is concerned with the decision making with predictive models acquired from data
called probabilistic decision tables. The methodology of probabilistic decision tables …

Variable Precision Bayesian Rough Set Model* Page 1 Variable Precision Bayesian Rough
Set Model* Dominik Slezak1,2 and Wojciech Ziarko1 1 Department of Computer Science …

To make up for the drawbacks of the rough set model on general relation, a majority
inclusion relation is defined and an error parameter/spl alpha/is introduced in order to give a …

The presentation introduces the basic ideas and investigates the stochastic approach to
rough set theory. The major aspects of the stochastic approach to rough set theory to be …

The objective of this paper is to provide a semantic framework for fuzzy sets in the theory of
rough sets. Rough membership functions are viewed as a special type of fuzzy membership …