In order to overcome the limitation of low efficiency of existing granularity reduction
algorithms in multi-granulation rough sets, based on matrix method, a fast granularity …

The notion of multi-granularity has been introduced into various mathematical models in
granular computing. For example, neighborhood rough sets can derive a good multi …

Multigranulation rough set theory is a desirable direction in the field of rough set, in which
upper and lower approximations are approximated by multiple granular structures. However …

Multigranulation rough set is a new expansion of the classical rough set since the former
uses a family of the binary relations instead of single one for the constructing of …

In order to obtain a better approximate approximation effect in multi-granulation rough set
model for target conception, an intuitionistic fuzzy rough set and a multi-granulation rough …

Multigranulation rough set, which is constructed by a family of equivalence relations has
attracted much attention, because it offers a theoretical framework for the problem solving in …

Exploring rough set theory in the viewpoint of multi-granulation gradually attracts scholars
attention in recent years. To handle uncertainty problems with grey information, in this paper …

Presently, the mechanism of multi-granularity has been frequently realized by various
mathematical tools in Granular Computing especially rough set. Nevertheless, as a key topic …

Multigranulation rough set (MGRS) theory has attracted much attention. However, with the
advent of big data era, the attribute values may often change dynamically, which leads to …

A simple multigranulation rough set approach is to approximate the target through a family of
binary relations. Optimistic and pessimistic multigranulation rough sets are two typical …