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.
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.
新的目标准则函数考虑了数据集样本的模糊隶属关系和样本几何分布两个方面的因素，使算法的鲁棒性和分类的正确性大大加强。
Two factors are considered in cluster-validity criterion to enhance the robustness of algorithm and the validity of clustering, one is fuzzy membership and the other is geometric property.
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 is a tool to deal with vague and uncertain data, therefore it becomes an important frame in DM.
文章前面部分仿真分析通过的各种交通流情况下的基于粗集理论的模糊控制方案表在系统中离线给出，以根据实时的交通流数据查表调用。
The System may adjust the control schemes by real time traffic data, which are off-line provided by the fuzzy traffic Decision table based on Rough Sets.
根据广义模糊集理论，提出了用于DICOM数据的动态边界检测算法。
According to theory of generalized fuzzy sets, the dynamic edge detection algorithm of DICOM Data was given.
基于模糊集的嵌入定理，对非精确数据的分布提出一种统计参数族，并给出相应的点估计方法。
Based on the embedding theorem of fuzzy sets, we consider a sort of parameter family for the distribution of imprecise data and propose the corresponding point estimation approach.
利用BP网的分类性可以将采集到的清晰数据集广义地分成模糊类。
The data can be broadly classified as fuzzy sets by using the classification property of the BP neural network.
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，在人工智能及数据挖掘等众多领域已经得到了广泛的应用。
Rough set theory is emerging as a powerful tool for dealing with vagueness and uncertainty of facts, which has important applications to artificial intelligence and data mining.
数据库中关联规则挖掘一直是人们研究的热点，而模糊集理论的应用又为这一领域注入了新的活力。
Mining association rules in databases is the hot point in people's researches and the application of fuzzy-set theory has added new energy into the field.
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 rough set theory is an important method for data mining of uncertain data.
我们模型的模糊和不确定的制约因素数据的模糊集理论。
We model the vague constraints and uncertain data by fuzzy set theory.
由于银行客户数据库中存在大量模糊和噪声数据，应用模糊集技术进行聚类分析，可以提高客户分类的效率和精确度。
There are lots of fuzzy and noisy data in bank database, by application of fuzzy set improve the efficiency and accuracy of customer classification.
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。
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.
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。
Combining rough set theory with fuzzy logic technology, this paper has presented a method of gaining fuzzy control rules based on measured data.
详细介绍了数据挖掘技术的常用方法，包括模糊理论、粗糙集理论、云理论、证据理论、人工神经网络、遗传算法以及归纳学习。
Mostly used methods are introduced in detail, including fuzzy method, rough sets theory, cloud theory, evidence theory, artificial neural networks, genetic algorithms and induction learning.
本文把模糊集理论和传统的关联挖掘结合在一起，提出了一种模糊关联数据挖掘算法。
In this paper, we connected fuzzy set theory with association mining, and proposed a fuzzy association data mining arithmetic.
另外，本文用模糊集理论对时间序列数据挖掘过程中的不确定性进行了处理，提出了一种模糊时序数据挖掘的框架。
Moreover, fuzzy sets theory is adopted in the dissertation to deal with the uncertainty of the mining process and a new fuzzy frame of TSDM is given then.
针对数据挖掘问题，将直觉模糊集与神经网络理论相结合，提出一种新的方法。
A new method was proposed for data mining problem which integrated intuitionistic fuzzy set and neural network theory.
运用模糊集技术处理商业银行中的非精确数据，对个人客户进行聚类分析，并通过实例分析了实现银行客户分类的整个过程。
A method of dealing with non-accurate data in commercial bank based on fuzzy set is presented, and clustering analysis of personal customer is introduced.
设计一种新型混合模糊神经推理系统，该系统仅从期望输入输出数据集即可达到获取知识、确定模糊初始规则基的目的。
A novel hybrid neural fuzzy inference system is presented. Only based on the desired input output data pairs, are the knowledge acquisition and initial fuzzy rule sets available.
针对流程工业数据的高维数、不确定的特点，研究适合处理流程数据的模糊集、粗糙集的粒度数据挖掘理论和方法。
According to the high dimensions and uncertainty of process industrial data, the fuzzy set and rough set of granularity data mining are studied for process data.
基于模糊集理论的多传感器数据融合，应用模糊集理论处理数据。
Based on fuzzy set theory, the multi-sensor data amalgamation adopted fuzzy set theory to deal with data.
为了提高模糊支持向量机在数据集上的训练效率，提出一种改进的基于密度聚类(DBSCAN)的模糊支持向量机算法。
In order to improve the training efficiency, an advanced Fuzzy Support Vector Machine (FSVM) algorithm based on the density clustering (DBSCAN) is proposed.
通过对实际数据的分析，获得了完整的模糊控制规则集。
A whole set of fuzzy control rules by analysing the actual data knowledge base have been set up.
基于方案风险数据实际，利用三角模糊数表示因素风险，结合模糊集理论和层次模型评判了各方案的风险大小；
Then these risk elements is denoted with tri-angle fuzzy number, and the risks value of all schemes are evaluated by the model combined fuzzy set theory and AHP.
改进传统窗口调节函数，结合模糊集理论和三维区域生长技术，提出并实现一种采用CT体数据场的人体器官提取新方法。
Based on the adjustment function, combining to fuzzy sets theory and 3d region growing technology, an approach for organ extraction from the ct human volumetric data was developed.
设计了一种基于粗糙集——模糊神经网络技术的数据挖掘与数据融合集成系统。
One kind of integrated data mining and data fusion system's model is designed with fuzzy neural network based on rough sets.
设计了一种基于粗糙集——模糊神经网络技术的数据挖掘与数据融合集成系统。
One kind of integrated data mining and data fusion system's model is designed with fuzzy neural network based on rough sets.
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