在粗糙集理论及粗糙模糊集理论中，上下近似及边界的求解与决策表属性约简是它们的核心内容。
In the rough set theory and rough-fuzzy set theory, computation of approximations and edge and attributes reduction of decision table is import part of them.
重新定义了近似空间内的一些概念，给出了加权粗糙集模型的约简概念，指出了加权系数的两种方法。
Some Approximate Space concepts were re-defined. The Reduction of Weighing Rough Set Model was stated, two methods for calculating weight were was given, too.
本文研究模糊近似空间与模糊拓扑空间之间的关系、基于模糊覆盖的粗糙集模型与约简等问题。
This paper discusses the relationships between a fuzzy approximation space and a fuzzy topology space. The approximations and reduction in fuzzy covering-based rough sets are also studied.
目前，人们对广义粗糙集的研究主要集中在集合的近似计算上，而真正利用广义粗糙集进行属性约简的研究还很少见。
The existing researches on generalized rough sets are mainly concentrated on set approximations; less effort has been made for attribute reduction.
目前，人们对广义粗糙集的研究主要集中在集合的近似计算上，而真正利用广义粗糙集进行属性约简的研究还很少见。
The existing researches on generalized rough sets are mainly concentrated on set approximations; less effort has been made for attribute reduction.
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