Variable Precision Rough Set Model Based On Similarity Dominance Degree

The incomplete ordered decision system is a complicated system which can be regarded as a combination of the incomplete information system and the ordered system. It can deal with the questions with preference ordered relation in our life. However, due to the incompleteness of the system, it is difficult to deal with the objects with more unknown values. This dissertation introduces the variable precision rough set model into the incomplete ordered decision system, proposes a notion of similarity dominance degree, and gives a variable precision rough set model based on similarity dominance degree; the properties of rough approximation operators of variable precision rough set model are discussed. Furthermore, we study the problem of attribute reduction by discussing the relative discernment of the sets and approximate dependability of the attribute sets.