$(O,G)$-granular variable precision fuzzy rough sets based on overlap and grouping functions
This work addresses theoretical extensions in fuzzy rough set theory for researchers in computational intelligence, but it appears incremental as it builds on existing concepts without broad practical impact.
The paper introduces $(O,G)$-granular variable precision fuzzy rough sets based on overlap and grouping functions, providing new expressions for approximation operators and extending results from granular variable precision fuzzy rough sets under certain conditions.
Since Bustince et al. introduced the concepts of overlap and grouping functions, these two types of aggregation functions have attracted a lot of interest in both theory and applications. In this paper, the depiction of $(O,G)$-granular variable precision fuzzy rough sets ($(O,G)$-GVPFRSs for short) is first given based on overlap and grouping functions. Meanwhile, to work out the approximation operators efficiently, we give another expression of upper and lower approximation operators by means of fuzzy implications and co-implications. Furthermore, starting from the perspective of construction methods, $(O,G)$-GVPFRSs are represented under diverse fuzzy relations. Finally, some conclusions on the granular variable precision fuzzy rough sets (GVPFRSs for short) are extended to $(O,G)$-GVPFRSs under some additional conditions.