Journal of Applied Mathematics
Volume 2012 (2012), Article ID 857590, 14 pages
Research Article

Parameterized Local Reduction of Decision Systems

Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, China

Received 25 May 2012; Revised 17 September 2012; Accepted 3 October 2012

Academic Editor: Juan Manuel Peña

Copyright © 2012 Degang Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One important and valuable topic in rough sets is attribute reduction of a decision system. The existing attribute reductions are designed to just keep confidence of every certain rule as they cannot identify key conditional attributes explicitly for special decision rules. In this paper, we develop the concept of -local reduction in order to offer a minimal description for special -possible decision rules. The approach of discernibility matrix is employed to investigate the structure of a -local reduction and compute all -local reductions. An example of medical diagnosis is employed to illustrate our idea of the -local reduction. Finally, numerical experiments are performed to show that our method proposed in this paper is feasible and valid.