基于粗糙集和模糊集的属性约简算法

粗糙集理论和模糊集理论都是用来处理不完整和不确定信息的理论，两者都可用来观察、测试数据并进行推理。虽然它们之间有一些重叠，但两者的着眼点和计算方法是不一样的，因此不能相互替代，而是必须结合起来使用。本文在研究粗糙集和模糊集理论的基础上将两者相结合，提出了一个新的属性约简算法，并给出了一个应用实例。

A Reduction Algorithm Based on Rough and Fuzzy Sets

Both the rough set and the fuzzy set theories can be used to deal with imprecise and incomplete information. For example, both of them are often used to observe, test and reason data Although they have some overlaps in doing so, they are different in some respects and calculations. Therefore, they can not be substituted by each other. Based on the research of the rough set and the fuzzy set theories, this paper proposes a new reduction algorithm by combining the two theories together and gives an illustrative example.