在属性测度概念的基础上，运用属性聚类网络方法解决模式识别问题。
Based on concepts of attribute measurement, we used attribute clustering network approach to resolve some problems of pattern recognition.
分析了目前的入侵检测技术，提出了使用聚类算法进行网络入侵检测的方法，并通过试验说明了该方法的应用效果。
This paper analyses the current intrusion detection techniques, brings forward a technique that applies cluster algorithm to network intrusion detection, and shows the effect through an experiment.
最后，分析了社会化标注中个性化信息推荐的研究，发现借助矩阵、聚类和网络的分析是三种主要思路。
Finally, studies on personalized information recommendation based on social tagging are analyzed, and find matrix, clustering and network analysis are three primarily methods.
提出了一种减聚类径向基函数神经网络的纺织空调送风风机故障诊断方法。
A new method of subtractive clustering RBF network for air condition breeze fan fault diagnosis is presented.
主题主要有聚类，稀疏编码，局限玻尔兹曼机和深度信念网络。
Topics include clustering, sparse coding, autoencoders, restricted Boltzmann machines, and deep belief networks.
在对径向基概率神经网络进行理论分析基础上，采用减法聚类方法确定它的隐中心矢量。
On the basis of analyzing RBPNN in theory, subtractive clustering is used to determine its hidden centric vector.
且生成网络直径、平均路径长度与网络平均聚类系数呈负相关关系。
The results show that the change of network diameter, average path length are negative correlation with that of the network clustering coefficient.
且生成网络直径、平均路径长度、度关联系数与网络平均聚类系数呈负相关。
The results show that the change of network diameter, average path length and degree correlation are negative correlation with that of the network clustering coefficient.
模糊聚类是目前知识发现(KDD)领域中的研究分支之一，而神经网络是用于聚类的良好工具。
Fuzzy cluster is one of the branches of knowledge discovery in database (KDD). And neural network is a good tool for clustering.
特别的，我还将介绍本地搜索算法的接近查询，和一个局部聚类的节点加权方法，以及网络的网络模型集成多个网络。
In particular, I will introduce a local search algorithm for proximity query, a node weighting method for local clustering, and the network of networks model for integrating multiple networks.
然后，采用改进的GHSOM网络对量化后的数据进行了聚类。
Then, an improved GHSOM network is used to cluster the quantized data.
此聚类算法可以在线地划分输入数据，逐点地更新聚类，自己组织模糊神经网络的结构。
This clustering algorithm can on-line partition the input data, pointwise update the clusters, and self-organize the fuzzy neural structure.
为了改进当前社会化标注系统在标签浏览和检索方面的弱点，提出一种基于加权网络分割的社会性标签聚类算法。
This paper proposes a clustering algorithm of social tags based on weighed network division for the purpose of improving browsing and retrieval in existing social annotation system.
这种无监督的聚类方法能够自动搜索最佳的网络输出节点数而获取图像中的目标数，从而完成对图像的自动分割。
This kind of unsupervised clustering method can search for the optimal number of output nodes automatically to get the number of textures in the 'image, and finish the automatic segmentation.
研究结果表明，按照提出的方法产生的复杂网络具有短的平均路径长度、较高的平均聚类系数、具备明显的齐次网络特性。
Our research shows that the complex network produced by our method has short average path length, high clustering coefficient, and some typical characters of a homogeneous network.
在网络信息检索中，基于文档向量空间的分类、聚类、排序与相关性反馈需要计算相似度。
In network information retrieval, based on document vector space, class, cluster, ranking and relevance feedback need to compute similarity.
在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，使网络结构得到优化。
A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure.
在RBF神经网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，从而使神经网络结构得到优化。
A learning algorithm of subtractive clustering method for RBFNN is used to obtain the parameters of radial basis function, so that RBFNN has an optimized structure.
算法基于标签节点的核心度和相似性对标签共现网络进行分割，并在聚类后自动生成该类的特征标签来代表该类簇。
The algorithm divides tag co -occurrence network based on tag node's centrality and similarity, and automatically generates a cluster feature tag after clustering to represent that cluster.
根据隐含语义索引（LSI）理论和动态自组织映射神经网络理论，提出了一种文本聚类的新方法。
This paper presents a new method of text clustering by using the latent semantic index (LSI) and self-organizing neural network (SNN).
为此本文提出了一种基于文档聚类的网络辅助浏览技术。
So the paper puts forward an Internet browsing assisted technology based on documental clustering.
通过邻接矩阵，计算网络的聚类系数。聚类系数是复杂网络中一个重要参量。
Through the adjacency matrix, computing networks, clustering coefficient. Clustering coefficient is a complex network, an important parameter.
本文通过分析现有入侵检测技术的优缺点，提出一种改进的聚类算法CLOPE将其应用于网络入侵检测。
This article through the analysis existing intrusion detection technology good and bad points, proposed one kind of improvement cluster algorithm CLOPE to apply to the network intrusion detection.
本文在分别介绍了传统分类和聚类算法之后，详细分析了基于ART神经网络的聚类算法。
After introducing the traditional methods of classification and clustering, this paper gives a particular analysis of the ART-based clustering method.
提出了一种新的动态模糊自组织神经网络模型(TGFCM)，并将其用于文本聚类中。
This paper proposed a new model of dynamic fuzzy Kohonen neural network (TGFCM), which was applied to the text clustering.
实验结果表明，算法对于真实道路网络中的对象聚类是高效的。
The experimental results indicate that the algorithms achieve high efficiency for clustering objects in real road network.
本文讨论了基于自组织特征映射网络聚类算法的基本原理，并指出了算法的缺陷。
In this paper, the basic principle of the clustering algorithm based on self-organizing feature map network is discussed, and pointed out its defects.
介绍了一种利用自组织特征映射(SOFM)网络的聚类功能进行全天星图识别的方法。
A method that applies the clustering function of SOFM (Self-Organizing Feature Maps) network is proposed for autonomous star pattern recognition.
提出了新颖的最优模糊聚类神经网络模型对机械手运动轨迹进行控制。
This paper presents a novel framework for trajectory tracking of robotic manipulators based on the optimal fuzzy clusting neural network system.
提出了新颖的最优模糊聚类神经网络模型对机械手运动轨迹进行控制。
This paper presents a novel framework for trajectory tracking of robotic manipulators based on the optimal fuzzy clusting neural network system.
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