Fuzzy set theory and rough set theory are two mathematical models of vagueness. In the case of fuzzy set theory elements are assigned membership degrees that usually belong to the (computable part of the) unit interval. In the case of rough set theory, one uses two approximations to "approach" vagueness. Assume that a cloud is a vague object. Then, one can assign membership degree to the points of R^3 to describe the cloud or you can use two ordinary objects (e.g., two cubes) so that the first is contained in the cloud and the second contains the cloud.

IMHO combining fuzzy and rough sets generates useless generalizations.  Just like "intuitionistic" fuzzy sets do not really broaden our understanding of vagueness.