Rough set theory is a new mathematical tool to deal with fuzzy and uncertain information.
粗糙集理论是一种新的处理模糊性和不确定性知识的数学工具。
Rough set theory is a new mathematical tool to deal with vagueness and Uncertainty problem after probability theory, fuzzy sets, mathematical theory of evidence.
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。
In this paper, we combine the fuzzy set theory with rough set theory by rough membership function and establish a relation between them.
通过粗糙隶属度函数，将粗集理论与模糊理论联系起来，建立一种粗集理论与模糊理论的关系。
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.
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。
This paper discussed the attribute reduction in rough set combined fuzzy relation theory, and then proposed a new attribute reduction algorithm and gave an illustrative example.
结合模糊关系的理论，对粗糙集理论的属性约简算法进行研究，提出了一个新的属性约简算法，并给出了一个应用实例。
Data mining is an important problem in KDD, and Rough set as a theory of set with fuzzy boundary is widely applied to infer classification rules from decision system.
数据挖掘是知识发现领域的一个重要问题，粗糙集理论是一种具有模糊边界的数据挖掘方法，它被广泛应用于决策系统的分类规则提取中。
The technology of attribute reduction based on the intuitionistic fuzzy rough set theory is described as to the problem of information loss in the process of discretization.
本文针对传统的离散化技术所造成的信息丢失问题，提出了利用直觉模糊粗糙集合理论来进行属性约简的方法。
Combining rough set theory with fuzzy logic technology, this paper has presented a method of gaining fuzzy control rules based on measured data.
将粗糙集理论与模糊逻辑技术相结合，提出了一种通过测量数据来获取模糊控制规则的方法。
Using fuzzy aggregation theory and rough set theory, this article puts out a weight allocation method based on impersonal message entropy.
借助模糊聚类技术和粗糙集理论提出了一个基于客观信息熵的多因素权重分配方法。
Rough Set Theory is another mathematical tool used for dealing with fuzzy and uncertain knowledge besides Probability Theory, fuzzy Set Theory and Evidence Theory.
粗集理论是继概率论、模糊集、证据理论之后的又一种处理模糊和不确定性知识的数学工具。
We combine the fuzzy set theory with rough set theory by rough membership function and establish a relation between them.
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。
Based on fuzzy rough set theory, it is liable to change the incomplete system into fuzzy information system and make the covert knowledge stand out in a way of decision regularity.
应用这种方法能够将不完备系统转化为模糊信息系统，然后利用模糊粗糙集理论，让隐藏在不完备信息系统中的知识以决策规则的形式表示出来。
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.
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。
Fuzzy rough set theory is an effective tool for reduction of data dimension, but there are few dimension reduction algorithms that are based on fuzzy rough set theory so far.
模糊粗糙集理论是解决数据集维数问题的有效工具，但基于模糊粗糙集的降维算法还不多。
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.
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 is a new math tool in dealing with fuzzy and uncertain knowledge.
粗糙集理论是一种处理模糊和不确定知识的新型数学工具。
Rough Set theory is a new mathematic tool to deal with fuzzy and uncertain knowledge.
粗糙集理论是一种新的处理模糊和不确定性知识的数学工具。
This paper puts forward a collaborative filtering algorithm based on rough set and fuzzy clustering which automatically fills vacant ratings through rough set theory.
提出了一种基于粗集和模糊聚类相结合的协同过滤推荐算法，通过粗集理论自动填补空缺评分降低数据稀疏性；
Fuzzy rough set theory is an important method for data mining of uncertain data.
模糊粗糙集理论是一种处理不确定性信息的重要的数据挖掘方法。
Fuzzy set theory and rough set theory has a strong complementary in dealing with uncertain problem.
模糊集理论与粗糙集理论在处理不确定性问题方面具有较强的互补性。
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.
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。
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