Affiliations: College of Mathematics & Computer Sciences, Hebei
University, Baoding 071002, Hebei, P.R. China. [email protected] | Department of Electrical & Computer Engineering,
University of Alberta Edmonton Canada and Systems Research Institute, Polish
Academy of Sciences, Warsaw, Poland. [email protected] | College of Mathematics & Computer Sciences, Hebei
University, Baoding 071002, Hebei, P.R. China. [email protected] | College of Mathematics & Computer Sciences, Hebei
University, Baoding 071002, Hebei, P.R. China. [email protected]
Note: [] Address for correspondence: Department of Electrical &
Computer Engineering University of Alberta Edmonton Canada and Systems Research
Institute Polish Academy of Sciences, Warsaw, Poland
Abstract: Given a widespread interest in rough sets as being applied to
various tasks of data analysis, it is not surprising at all that we have
witnessed a wave of further generalizations and algorithmic enhancements of
this original concept. In this study, we investigate an idea of rough fuzzy
random sets. This construct provides us with a certain generalization of rough
sets by introducing the concept of inclusion degree. The underlying objective
behind this development is to address the problems which involve co-existing
factors of fuzziness and randomness thus giving rise to a notion of the fuzzy
random approximation space based on inclusion degree. Some essential properties
of rough approximation operators of such rough fuzzy random sets are discussed.
Further theoretical foundations for the formation of rules constructed on a
basis of available decision tables are offered as well.
