A method of knowledge reduction based on generalized rough sets

To meet the practical demand of the rough set theory in knowledge reduction, the paper establishes a method of knowledge reduction based on generalized rough sets. Firstly, the paper proves that an important value of generalized rough sets is based on arbitrary binary relations on a universal set, which may extend applications of the classical rough set theory, and then presents the decision theorem of knowledge reduction and discernible matrix based on some general binary relations. Finally, the validity of the method is verified by the application of a practical knowledge system, which can accurately abstract a minimal attribute set. The major contributions of this paper are the method of knowledge reduction based on generalized rough sets may overcome the shortage of the classical rough set theory, and extend many practical applications in various areas.