关键词: 区间值序信息系统, 差别信息树, 压缩储存, 属性约简

Abstract: Attribute reduction is a hot topic in rough set, and discernibility matrix is an effective method to get attribute reduction. However, the discernibility matrix contains duplicate elements, which increases the time needed to get the reduction. The discernibility information tree solves the issue, and realizes the compression storage of the non-empty elements in the discernibility matrix. Unfortunately, the discernibility information tree is based on the discernibility matrix under the equivalence relation, and does not consider the situation of the ordered decision information system. In this paper, a discernibility information tree is proposed based on distinguishable matrix in interval-valued ordered information systems, which solves the problem of redundant elements in the distinguishable matrix and realizes the compression storage of non-empty elements in the distinguishable matrix. Furthermore, the related theorem of the tree is obtained and verified carefully. And, a complete attribute reduction method is given based on the discernibility information tree of the interval-valued ordered information system. Finally, an empirical analysis is addressed, which verifies the feasibility and effectiveness of the method.