Rough set theory is the tool to solve those problems.
粗集理论由于其自身的特点恰好能够解决这三个问题。
Attribute reduction is a research focus in rough set theory.
属性约简是粗糙集理论中的一个研究重点。
We propose a data mining model based on clustering and rough set.
提出了一种基于聚类和粗糙集的数据挖掘模型。
The attribute reduction is one of the cores of Rough Set (RS) theory.
属性约简是粗糙集(RS)理论的核心内容之一。
The equivalence relation is the basic Concept of the rough set theory.
等价关系是粗集理论中的一个重要概念。
This paper presents a rough set theory based on the text classification.
文章提出了一种基于粗糙集理论的文本分类方法。
Rough set theory is a novel mathematical tool dealing vagueness and uncertainty.
粗糙集理论是处理模糊和不确定性问题的新的数学工具。
Reduction and core are two important concepts and significantly applied in rough set.
约简与核是粗集中的两个重要概念，它具有重要的应用。
Rough set theory is a new mathematical approach to deal with vagueness and uncertainty.
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。
Proposed an algorithm of attribute reduction based on attribute importance of rough set.
提出一种基于粗糙集属性重要性的属性约简算法。
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。
In this paper, a new extension of rough set based on modified tolerance relation is presented.
提出了一种基于修正容差关系的扩充粗糙集模型。
On the basis of fuzzy clustering and rough set, an algorithm for extracting fuzzy rules was 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。
Rough set theory has been aiming at data analysis problems involving uncertain or imprecise information.
粗糙集理论一直致力于研究不确定或不精确信息的数据分析问题。
Rough Set is a tool to deal with vague and uncertain data, therefore it becomes an important frame in DM.
粗集是一种处理模糊和不确定性数据的工具，因而成为数据挖掘中的重要框架。
Rough set theory is used to mine the knowledge and get the essence characteristics of the continuous data.
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, as an effective tool to deal with vagueness and uncertainty, is effective to the time series data mining.
粗糙集理论作为一种处理模糊和不确定性问题的有效工具，对时间序列的数据挖掘是有效的。
Rough Set is a new mathematical tool to deal with fuzzy and uncertain knowledge. It has strong knowledge obtaining ability.
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。
A rough set based data mining system named RSDMS is put forward and realized after the analysis of algorithms in rough set.
在分析了粗集的各种算法之后提出并实现了一个基于粗集的数据挖掘系统RSDMS。
For a multifactor weather prediction problem, this paper constructs a new model of fuzzy neural network based on rough set.
针对民用机场多因素气象预测问题的复杂性，该文构建出一种基于粗糙集的模糊神经网络模型。
An example resulting from running is given, which shows the practical significance to the applications of rough set theory.
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。
As the extension of rough set, variable precision rough set reflects the difference of degrees of overlap of kinds and sets.
而可变精度粗糙集作为对经典粗糙集理论的扩展，体现了等价类与集合的重叠度程度上的差别。
This paper discusses a new intelligent control method called rough control, and presents the basic concepts of rough set theory.
本文讨论了一种新型的智能控制方法—粗糙控制，介绍了粗糙集合理论的基本概念。
In this paper, begin with agent technology - rough set theory and ANN technology have been applied to research on financial risk.
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。
The median filtering method based upon Rough set theory was applied to the sonar image processing, and the demonstration was given.
将基于粗集理论的中值滤波应用于声呐图像处理中，给出了实验结果。
In this paper, we discuss rough set approximation under granulation, and establish positive approximation under dynamic granulation.
本文讨论了粒度意义下的粗糙集近似，并定义了动态粒度下的正向近似。
A rough set model to mine default rules was presented in order to reason and solve the decision question with incomplete information.
提出了一种基于粗集的缺省规则挖掘模型，以利于在信息不完备情况下进行推理和决策。
Aiming at the problem of data sparsity for collaborative filtering, a novel rough set-based collaborative filtering algorithm is proposed.
针对协同过滤中的数据稀疏问题，提出了一种基于粗集的协同过滤算法。
The Out-lier algorithm based on density and attribution classical discrepant data protocol algorithm based on rough set theory were presented.
提出了一种基于密度的孤立点因子算法和一种基于粗集理论的属性类别差异数据归约算法。
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.
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。
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