Matrix Approaches for Covering-Based Multigranulation Fuzzy Rough Set Models

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 large covering using representation approaches. Hence, presenting novel methods them quickly our motivation this paper. In article, we study matrix representations save time processing. Firstly, some new matrices operations are proposed. Then, optimistic CMFRSs presented. Moreover, approaches computing pessimistic also Finally, experiments proposed illustrate effectiveness