Abstract: Sequential three-way decision is an effective way to solve problems under multiple levels granularity.Dominance-equivalence relation based rough set approach can be used to handle classification problems for conditional attri-butes with preference ordered,extract related information,approximate target concepts and finally form the decision-making knowledge.The traditional dominance relation-based rough sets model is very time consuming for knowledge reduction and extraction,however,most of current sequential three-way decision models are limited to information systems of symbolic attributes,which can not process continuous and ordinal values effectively,and will cause a certain degree loss of information.Therefore,this paper applied the idea of sequential three-way decisions to the dominance relation-based rough sets models,defined a new attribute reduction method based on sequential three-way decisions and the corresponding attribute importance measure,and thenaccelerated the processing of information systems with ordinal attributes.Finally,the efficiency of knowledge reduction is improved through multiple granularity representations and relationships.Several UCI data sets are selected for experiments.The results show that the proposed sequential three-decision method based on dominance relations can reduce the time consumption noticeably and guarantee the quality of the attribute reduction.

Key words: Attribute reduction, Decision theory rough set, Dominance relation, Rough set, Sequential three-way decisions