Comparative Studies of Knowledge Reductions in Inconsistent Systems
Mi Ju · Mohu xitong yu shuxue · 2003
Due to issues such as noise in data, compact representation and prediction capability, many types of knowledge reduction have been proposed and applied in inconsistent decision information systems. It is thus important to clarify the relationships among the existing types of knowledge reduction. The main objective of this paper is to find and prove static relationships among classical types of knowledge reduction in inconsistent decision information systems. It is proved that distribution reduction is both β upper distribution reduction and β lower distribution reduction. Under certain conditions, β upper distribution reduction is equivalent to the assignment reduction and β lower distribution reduction is equivalent to maximum distribution reduction.