粗糙集的近似约简及其算法 关键词：粗糙集；近似属性约简；约简算法 [gap=946]Key words：rough set；approximate attribute reduction；reduction algorithm
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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.
其主要内容包括近似集、决策系统、数据预处理以及属性约简等等，是一种处理不完整，不精确数据的有效方法。
The main contents include the approximation set, decision systems, data preprocessing and attribute reduction and so on. It is a effective method of dealing with incomplete, inaccurate data.
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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