A dynamic framework for updating approximations with increasing or decreasing objects in multi-granulation rough sets

Abstract

The data we need to deal with is getting bigger and bigger in recent years, and the same happens to multi-granulation rough set, so updated schemes have been proposed with the variation of attributes or attribute values in multi-granulation rough sets, this paper puts forward a dynamic mechanism to update the approximations of multi-granulation rough sets when adding or deleting objects. Firstly, the relationships between the original approximations and updated approximations are explored when adding or deleting objects in multi-granulation rough sets, and the dynamic processes of updating optimistic and pessimistic multi-granulation rough approximations are proposed. Secondly, two corresponding dynamic algorithms are proposed to update the lower and upper approximations of optimistic and pessimistic multi-granulation rough sets. Finally, a great quantity of experiments had been implemented, and the results indicate that two dynamic algorithms proposed are more effective than the static algorithm.