  In a dynamic environment, knowledge reduction of information systems with
variations of object sets, attribute sets and attribute values is an important
topic of rough set theory, and related family-based attribute reduction of
dynamic covering information systems when refining and coarsening coverings has
attracted little attention. In this paper, firstly, we introduce the concepts
of the refinement and coarsening of a covering and provide the mechanisms of
updating related families of dynamic covering decision information systems with
refining and coarsening coverings. Meanwhile, we investigate how to construct
attribute reducts with the updated related families and propose the incremental
algorithms for computing attribute reducts of dynamic covering decision
information systems. Finally, the experimental results verify that the proposed
algorithms are more effective than the non-incremental algorithms for attribute
reduction of dynamic covering decision information systems in terms of
stability and computational time.
