Artificial immune network clustering is often ineffective when there is noise or undefined cluster boundary in the data.
当数据集聚类边界不清晰或存在噪声干扰时，人工免疫网络聚类算法通常无法获得有效的聚类划分。
By analyzing ART2 neural network clustering algorithm, an improved ART2 neural network clustering algorithm was proposed.
分析了现有ART2网络存在的问题，提出了一种改进的ART2算法。
This case USES combined with fuzzy clustering and generalized regression neural network clustering algorithm for intrusion data classification.
本案例采用结合模糊聚类和广义神经网络回归的聚类算法对入侵数据进行分类。
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、平均路径长度与网络平均聚类系数呈负相关关系。
Reasonable clustering analysis of data done by clonal network can be obtained when the strategy of immunity cloning is applied to network clustering.
将免疫克隆策略用于网络结构的聚类中，能够得到克隆网络对数据进行合理的聚类分析。
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.
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。
This paper studies the wireless sensor network clustering system, analysis of several typical clustering algorithm based on the traditional clustering algorithm was improved.
本文主要研究无线传感器网络中的分簇机制，在分析了典型分簇算法的基础上，对传统分簇算法进行了改进。
Whereas, an improved ART2 neural network clustering algorithm is proposed to realize the clustering of dynamic samples, and the simulation results are given out at the same time.
鉴于此，本文又提出了一种改进的ART2网络学习算法来实现动态样本的聚类，同时给出了该方法的实验仿真结果。
Clustering across a WAN is not a problem, as long as you have sufficient WAN network bandwidth to handle the replication traffic.
只要您有足够的WAN带宽处理复制流量，也可以实现跨wan网络的集群。
When clustering was introduced to WebSphere MQ, the retronym point-to-point network was used to differentiate between a cluster and the classic MQ network topology.
当WebSphereMQ引入集群的概念时，新词点对点网络被用于区分集群和一般的MQ网络拓扑。
This neural network pattern recognition can be applied to feature extraction, clustering analysis, edge detection, signal enhancement and noise suppression, data compression, such as various links.
这样神经网络可应用于模式识别的特征提取、聚类分析、边缘检测、信号增强以及噪声抑制、数据压缩等各个环节。
The Network Deployment configuration provides clustering support for this purpose.
Net workDeployment配置提供了用于此用途的集群支持。
Further support has been added in the area of clustering and federation of servers allowing for additional Network Deployment topologies.
在集群和服务器联合方面添加了更深入的支持，支持附加的Network Deployment拓扑。
Finally, studies on personalized information recommendation based on social tagging are analyzed, and find matrix, clustering and network analysis are three primarily methods.
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。
A new method of subtractive clustering RBF network for air condition breeze fan fault diagnosis is presented.
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。
Clustering Algorithm is a kind of key technique used to reduce energy consumption, which can increase network scalability and lifetime.
成簇算法是传感器网络中减少能量消耗的一种关键技术，它能够增强网络的扩展性和延长网络的生存时间。
Fuzzy cluster is one of the branches of knowledge discovery in database (KDD). And neural network is a good tool for clustering.
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。
This paper proposes a novel Weight Clustering Algorithm for mobile self-organized network.
本文提出了一种新型的适用于移动自组织网络的权值分群算法。
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.
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。
Through the adjacency matrix, computing networks, clustering coefficient. Clustering coefficient is a complex network, an important parameter.
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。
Experimental results show that our algorithm has a better performance on network lifetime than the common clustering algorithms.
实验结果表明，新算法较常见分簇算法更能够延长网络寿命。
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.
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。
Based on concepts of attribute measurement, we used attribute clustering network approach to resolve some problems of pattern recognition.
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。
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.
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。
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。
This paper proposed a new model of dynamic fuzzy Kohonen neural network (TGFCM), which was applied to the text clustering.
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。
The experimental results indicate that the algorithms achieve high efficiency for clustering objects in real road network.
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。
In this paper, the basic principle of the clustering algorithm based on self-organizing feature map network is discussed, and pointed out its defects.
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。
A method that applies the clustering function of SOFM (Self-Organizing Feature Maps) network is proposed for autonomous star pattern recognition.
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.
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。
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