结合粗糙集和模糊神经网络提出了一种粗糙模糊神经网络识别器的模型。
A model of rough fuzzy neural network classifier was presented by combining rough set and fuzzy neural network.
粗糙集的不确定性度量方法，目前主要包括粗糙集的粗糙度、粗糙熵、模糊度和模糊熵。
Rougness, rough entropy, fuzziness, and fuzzy entropy are major methods for measuring the uncertainty of rough sets.
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.
本文介绍了粗糙集和模糊粗糙集的上下近似。
This paper introduces the lower and upper approximations operator of rough sets and fuzzy sets.
粗糙集理论和模糊集理论是处理不确定和不精确问题的两种数学工具，它们有很强的互补性，将这两种理论相互融合可以建立粗糙模糊集模型。
Rough set theory and fuzzy set theory are two complementary mathematical tools for dealing with imprecision and uncertainty. Rough-fuzzy sets model is established by them.
在粗糙集的基本概念上定义了二维离散空间中的粗糙区域和粗糙模型，基于粗糙模型描述了二维离散空间中的模糊地理对象，并给出了粗糙区域的类型。
Rough model is proposed to build vague regions based on upper and lower approximate sets of rough set theory after the definition of rough regions and rough 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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