粗糙集理论是继概率论、模糊集、证据理论之后的又一个处理不确定性问题的新型数学工具。
Rough set theory is a new mathematical tool to deal with vagueness and Uncertainty problem after probability theory, fuzzy sets, mathematical theory of evidence.
首先本文将粗糙集理论与模糊集理论进行比较，通过粗糙隶属函数将模糊集的研究方法引入到粗糙集的研究中。
In this paper, firstly we compare RST with fuzzy Sets Theory and introduce fuzzy method into the study of RST by the rough membership function.
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.
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