属性约简是粗糙集理论的核心内容。
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.
属性约简是粗糙集理论的核心内容之一。
Attributes reduction was one of the key problems in 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.
属性约简是粗糙集理论中的一个重要课题。
Reduction of attribute is another important subject in Rough Set theory.
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.
本文首次将粗糙集理论应用于林业信息管理之中。
This paper first apply the rough set theory to forestry information manage.
利用粗糙集理论可以从已知数据中挖掘决策规则。
Decision rules can be mined from given data using rough set theory.
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.
属性约简问题是粗糙集理论中一个核心的研究课题。
Attribute reduction is a core subject in the domain of rough set theory.
数据约简是粗糙集理论中一个非常重要的研究课题。
Data reduction is one of important research issue in rough set theory.
将广义覆盖粗糙集理论及其计算运用到信息检索模型。
This article applies the generalized covering rough set theory to information retrieval model.
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.
粗糙集理论与证据理论都是处理不确定性知识的数学工具。
Both rough set theory and evidence theory are the math tools for dealing with uncertain knowledge.
简约的计算是基于粗糙集理论的数据采掘研究的关键问题。
Reduct calculation is the key issue of the research of rough set based data mining.
分析了基于粗糙集理论的装配知识发现中属性归约的过程。
The process of attribute reduction is analyzed in assembly knowledge discovery based on rough set.
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.
提出了一种粗糙集理论与神经网络集成的风机故障诊断方法。
A new method of rough set and neural network for fan trouble diagnosis is presented.
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 theory has been aiming at data analysis problems involving uncertain or imprecise information.
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.
本文对两种非经典数学方法：粗糙集理论和云理论进行了介绍和分析。
The paper introduces and then analyzes the two non-classical mathematics methods: the rough theory and the cloud theory.
该策略利用粗糙集理论对数据样本进行数据浓缩，提取初步的诊断规则。
This tactics carry out data compaction on data samples and extract initial diagnostic rule by using rough set theory.
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.
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.
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.
这些不仅为燃煤发热量预测提供了一种新的方法，而且也拓宽了粗糙集理论的应用领域。
All these not only provides a new method to forecast the quantity of heat, but also develops the application fields of RS.
提出用粗糙集理论简化这些因素，然后采用径向基函数网络对连铸板坯缺陷进行预报诊断。
This research USES rough sets to reduce this factors, then adopts radial basis function networks to predict and diagnose the continuous casting slab defect.
运用简单相关、灰色关联分析方法和粗糙集理论，分析了土壤特性对小麦籽粒产量的影响。
The effect extent of soil property for wheat yield was analyzed by using correlation analysis, grey associate analysis and rough sets theory.
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 theory, as an effective tool to deal with vagueness and uncertainty, is effective to the time series data mining.
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