Extended Probabilistic Rough Sets Under a Strict Dominance Relation

In order to handle inconsistencies in ordinal and monotonic information systems, the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) has been proposed and successfully applied in real decision making. However, there exists an error spread of inconsistencies in VC-DRSA. In this paper, we firstly induce a strict-dominance relation into Variable-Precision Rough Sets (VPRS). Two new equivalence relations are constructed by the strict-dominance relation. Then, we propose a new model, e.g., Strict-Dominance-based Probabilistic Rough Set Approach (SD-PRSA), which may release the error spread of inconsistencies. An example of performance evaluation in a university is employed to illustrate SD-PRSA and validate the advantage of SD-PRSA compared with VC-DRSA.