Novel Approaches to Knowledge Reduction in Inconsistent Decision Systems

This paper deals with approaches to knowledge reduction in inconsistent decision systems. The judgment theorem with respect to attribute reduction is obtained, from which the novel approaches to maximum distribution reduction, distribution reduction and possible reduction are presented. In addition, its time complexity is analyzed in detail. Experimental results show that the reduction algorithms are more efficient than those existing algorithms.