Sorting Decision Model for Dynamic Fault Tolerance Based on Dominance Relation Rough Set

To enhance the fault-tolerant capacity of the dominance relation rough set model in solving sorting decision problems, three efficient sorting decision algorithms are proposed by regarding the fault-tolerant processing as a dynamic adjusting process according to the fault tolerance direction of the user's preference, i.e., upward, downward, or synthesis of the both. The boundary objects are initially ranked by the proposed algorithms, and the obtained results are adjusted using the coverage information as the heuristic criteria to achieve a accurate or near accurate sorting of the object finally. In contrast to the variable-consistency dominance-based rough set approach (VC-DRSA), the proposed algorithms do not need prior domain knowledge to determine and adjust a threshold. Application of the algorithms to wine quality dataset show that the proposed methods can achieve a 21.34% improvement in average sorting accuracy and a 50.91% reduction in average mis-sorting cost, compared with the existing methods.