Since the multigranulation rough sets (MGRS) can be considered as the compositions of multi– independent Pawlak’s rough sets, the multigranulation rough set rules (MGRS rules) are then the compositions of decision rules, which are supported by multi–independent Pawlak’s rough sets. To measure MGRS rules, both the local and global views are employed in this paper. In local view, the support, cer...

Multigranulation rough set theory is one of the most effective tools for data analysis and mining in multicriteria information systems. Six types covering-based multigranulation fuzzy (CMFRS) models have been constructed through β -neighborhoods or measures. However, it often time-consuming to compute these CMFRS with a ...

As big data often contains a significant amount of uncertain, unstructured, and imprecise that are structurally complex incomplete, traditional attribute reduction methods less effective when applied to large-scale incomplete information systems extract knowledge. Multigranular computing provides powerful tool for use in analysis conducted at different levels granularity. In this article, we pr...

The notion of rough sets introduced by Pawlak has been a successful model to capture impreciseness in data and has numerous applications. Since then it has been extended in several ways. The basic rough set introduced by Pawlak is a single granulation model from the granular computing point of view. Recently, this has been extended to two types of multigranular rough set models. Pawlak and Novo...