传统的粗糙集理论只能对数据库中的离散属性进行处理，所以对存在连续属性的数据库必须进行离散化处理。
The traditional rough set theory can only deal with the discrete attribute in a database, so it is necessary to deal with the consistent attribute when the consistent attributes exist in a database.
粗糙关系数据库模型从本质上来说就是多值信息系统，它继承和扩展了经典的粗糙集理论，但与经典粗糙集理论又有着很大的不同。
Rough relational database model is Multi-valued information system essentially, inheriting and extending classical rough sets theory. But there is much difference between them.
文章提出了一种基于粗糙集理论的文本分类方法。
This paper presents a rough set theory based on the text classification.
属性约简是粗糙集(RS)理论的核心内容之一。
The attribute reduction is one of the cores of Rough Set (RS) theory.
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 fuzzy and uncertain information.
粗糙集理论是一种处理模糊和不确定性问题的新的数学方法。
Rough set theory is a new mathematical approach to deal with vagueness and uncertainty.
约简与核是粗糙集理论的两个重要概念，而直接由定义来计算约简与核是一个典型的NP难题。
Reduction and core are two important concepts in rough set theory, while computing reductions and core according to the definitions directly is a typical NP problem.
今后的工作是开发基于这种粗糙集模型的实用软件系统和理论上的深入研究。
For the future, realistic soft system based on this model of Rough Sets will be theoretically lucubrated and exploited.
粗糙集理论是处理模糊和不确定性问题的新的数学工具。
Rough set theory is a novel mathematical tool dealing vagueness and uncertainty.
粗糙集理论由于其独特的知识表示方法在数据预处理方面有着得天独厚的优势，同时也成为数据库中知识发现的有效手段。
Rough Sets theory has great superiority in Data Preprocessing because of its particular expression of knowledge, as well as it makes an effective means of knowledge Discovery in Database.
最后给出实际例子的程序运行结果，对推动粗糙集理论在具体实践中应用和普及，具有实际意义。
An example resulting from running is given, which shows the practical significance to the applications of rough set theory.
属性约简是粗糙集理论中的一个研究重点。
Attribute reduction is a research focus in rough set theory.
粗糙集理论是一种处理模糊和不精确知识的数学工具，它具有很强的知识获取能力。
Rough Set is a new mathematical tool to deal with fuzzy and uncertain knowledge. It has strong knowledge obtaining ability.
为了在故障诊断信息不一致的情况下提取简单有效的诊断规则，提出了一种基于粗糙集理论的决策规则提取方法。
In order to extract simple and effective diagnostic rales from inconsistent diagnostic information, an extraction method of decision rules for fault diagnosis based on rough set theory is proposed.
提出了一种基于模糊软分类和粗糙集理论来提取模糊规则的一种算法。
On the basis of fuzzy clustering and rough set, an algorithm for extracting fuzzy rules was proposed.
离散类别确定后再应用粗糙集理论对其进行知识挖掘，可得到连续数据的本质特性。
Rough set theory is used to mine the knowledge and get the essence characteristics of the continuous data.
针对上述所提证据理论的局限性，本文提出了一种基于粗糙集理论的证据获取的新方法，并对证据合成和应用进行了研究。
To the limitation of evidence theory mentioned above, this paper proposes a new way of knowledge acquirement and also presents a valuable method of the evidence combination and application.
运用粗集理论对逻辑函数进行知识表达的方法，提出了基于粗糙集的组合逻辑优化方法，并给出了相应的算法。
Rough set-based method of combinatory logic optimization was presented by using knowledge expression of logic function with rough set theory, and its corresponding algorithm was given, also.
该方法拓展了粗糙集理论的应用领域，并为焊接建模提供了一种新方法，具有较大的应用潜力。
So it enlarges the application area of rough set theory and provides a new method for modeling in welding area, and has a large potential of wide application.
为了避免传统的权值确定方法所带来的主观性影响，将粗糙集理论引入可拓权重系数的求解过程中，使权系数问题转化为属性重要度评价问题。
To avoid the excessive subjectivity influenced by the conventional determination methods of weight factor, the rough set was introduced to the solution of the weight factor in the extenics evaluation.
本文简要介绍了数据挖掘技术的基本原理和主要方法，以及粗糙集理论的基本原理，并给出了一个利用数据挖掘技术对肺部肿瘤进行诊断评价的应用实例。
This paper briefly introduces the principles and methods of the data mining and the rough set theory, and gives an example on the diagnosis and evaluation of the lung tumor.
以对琼海市土地适宜性评价为例，引用了粗糙集理论和云理论相结合的方法。
The paper take the land suitability appraise of Qionghai as a sample, using the method that combine the cloud theory and the rough theory.
属性约简是粗糙集理论的核心内容。
作者研究了粗糙集扩展理论，提出了一种多层粗糙集模型CBM-RS。 该模型是一种基于覆盖的扩展的多层粗糙集模型。
The thesis studies the generalized rough set models and proposes a multi-level rough set approximation model CBM-RS based on a covering of the universe.
本文的研究是从智能理论角度着手，把粗糙集理论与神经网络技术应用于我国上市公司财务预警的研究当中。
In this paper, begin with agent technology - rough set theory and ANN technology have been applied to research on financial risk.
知识约简是粗糙集理论的重要研究内容。
Knowledge reduction is one of important issues in rough set theory.
本文回顾了粗糙集理论，介绍了粗糙集模型的主要概念，系统总结了粗糙集理论与其他智能方法的融合并介绍了粗糙集理论的硬件实现方法。
This paper reviews the theory of rough set, introduces the main concept of rough set theory and discusses the application of the rough set theory mixing with the other intelligent methods.
连续属性的离散化是粗糙集理论的主要问题之一。
The discretization of real value attributes is one of the most main problems in rough sets theory.
提出了粗糙信息熵的概念，证明了粗糙集理论中知识不确定性与其所对应的粗糙信息熵之间的单调关系。
The concept of rough entropy is proposed. The monotony between the uncertainty of knowledge in the rough set theory and its corresponding rough entropy is proved.
提出了粗糙信息熵的概念，证明了粗糙集理论中知识不确定性与其所对应的粗糙信息熵之间的单调关系。
The concept of rough entropy is proposed. The monotony between the uncertainty of knowledge in the rough set theory and its corresponding rough entropy is proved.
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