Attribute reduction based on interval valued fuzzy granules

Recently, most of the work of interval valued fuzzy rough sets has been focused on the knowledge representation. Less work on the application of interval valued fuzzy rough sets (IVFRSs), such as attribute reduction IVFRSs, was done. In this paper an approach of attribute reduction based on Interval Valued Fuzzy Discernibility Matrix is proposed. First, discernibility matrix, which is vital to finding reducts, is designed in the IVFRS framework. Then, an algorithm to find reducts is proposed. Finally, the numerical experiments show the workability and usefulness of the proposed approach.