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.
在可能性测度的粗糙集解释基础上，给出了模糊集与粗糙集的一个转化算法，从而建立了两种非经典集合之间的关系。
Based on the interpretation of possibility measure based on rough set, we give an conversion algorithm of fuzzy set and rough set, thus establish a connection between these two non-classical set.
通过粗隶属函数，将粗糙集理论与模糊集理论联系起来，建立一种粗糙集理论与模糊集理论间的关系。
We combine the fuzzy set theory with rough set theory by rough membership function and establish a relation between them.
把粗糙集理论与基于概率统计ID3算法结合建立粗糙集约简模型，可处理不精确和模糊数据集信息。
The rough sets reduction model is established by integrating rough sets theory with ID3 algorithm based on statistics, uncertainty fuzzy data set information can be processed with the model.
人们将粗糙集理论与模糊集理论相结合，提出了粗糙模糊集模型和模糊粗糙集模型，并给出了相应的不确定性度量方法。
By combining fuzzy set theory and rough set theory, rough fuzzy set model and fuzzy rough set model were proposed, and the uncertain measurement approaches were established.
人们将粗糙集理论与模糊集理论相结合，提出了粗糙模糊集模型和模糊粗糙集模型，并给出了相应的不确定性度量方法。
By combining fuzzy set theory and rough set theory, rough fuzzy set model and fuzzy rough set model were proposed, and the uncertain measurement approaches were established.
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