In this paper, three types of (philosophical, optimistic and pessimistic) multigranulation single valued neutrosophic (SVN) covering-based rough set models are presented, and these three models are applied to the problem of multi-criteria group decision making (MCGDM).Firstly, a type of SVN covering-based rough set model is proposed.Based on this rough set model, three types of mult...

Many researchers have combined rough set theory and fuzzy set theory in order to easily approach problems of imprecision and uncertainty. Covering-based rough sets are one of the important generalizations of classical rough sets. Naturally, covering-based fuzzy rough sets can be studied as a combination of covering-based rough set theory and fuzzy set theory. It is clear that Pawlak’s rough set...

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 ...

Rough set theory is a very effective tool to deal with granularity and vagueness in information systems. Covering-based rough set theory is an extension of classical rough set theory. In this paper, firstly we present the characteristics of the reducible element and the minimal description covering-based rough sets through downsets. Then we establish lattices and topological spaces in coveringb...

The classical multigranulation rough set (MGRS) theory offers a formal theoretical framework for solving the complex problem under multigranulation environment. However, it is noticeable that MGRS theory cannot be applied in multi-source information systems with a covering environment in the real world. To address this issue, we firstly present in this paper three types of covering based multig...

Covering rough sets conceptualize different types of features with their respective generated coverings. By integrating these coverings into a single covering, covering set-based feature selection finds valuable from mixed decision system symbolic, real-valued, missing-valued and set-valued features. Existing approaches to selection, however, are intractable handle large data. Therefore, an eff...