Updating Approximations of VPRS Model based on Dominance Relations

Jiajia HOU, Yan LI*, Yan ZHAN, Liang WANG

Key Lab. In Machine Learning and Computational Intelligence, College of Mathematics and Computer Science, Hebei University, Baoding City, Hebei Province, China

*Corresponding author

Abstract: In real world problems, the collected data vary from time to time, and therefore, the approximations of a concept by a variable precision rough set model (VPRS) should be correspondingly updated. This paper focuses on developing incremental method to ｕｐｄａｔｅ set approximations of VPRS based on dominance relations. Under dynamic environments where an object is inserted ｏｒ deleted, we present the updating principles and then develop the incremental method for updating approximation sets. The related theoretical results are presented with proofs, and illustrative examples are also given to support the effectiveness of the proposed method.

Keywords: Variable Precision Rough Set; Dominance Relation; Set Approximation; Dynamic Information Systems; Incremental ｕｐｄａｔｅ