cluster number
英 [ˈklʌstə(r) ˈnʌmbə(r)]
美 [ˈklʌstər ˈnʌmbər]
网络 簇号
双语例句
- This is the cluster number within the network.
这是网络内的群集号。 - First, the sampling theorem is given and proved, and the minimum sample size is derived according to the smallest duster and cluster number.
首先，给出采样数定理及其证明，并推导出与聚类类别数和最小聚类相关的最小采样数目； - The paper also proposes mathematical models for measuring Rosa roxburghii yield based on cluster number, cluster height, or crown width.
同时，提出了以丛数、丛高或冠幅为计量单位，通过各种数学模型估测刺梨产量的计量方法。 - Cluster Number-three digits assigned by network administration
群集号&网络管理赋值的三位数 - The method can overcome the shortcoming of sensitivity to the order of input dates and necessity to know the cluster number before it works, and it also can reduce the number of parameters '.
该方法克服了聚类算法中对数据输入顺序敏感和需要预设聚类数目的缺点，减少了所需参数个数。 - Some available algorithms are reviewed and a mathematical morphology based clustering algorithm ( MMC) is presented in this paper. Clusters with arbitrary shape can be discovered by using MMC algorithm, and the optimal cluster number is automatically determined by a heuristic method.
在分析已有聚类算法的基础上，提出了一种基于数学形态学的聚类算法，该算法能够处理任意形状的聚类，采用启发式方法自动确定最优聚类数。 - As for fuzzy c-means clustering algorithm, we introduced the concept of validity function to solve problems about partial optimization and how to decide the cluster number.
在模糊C均值聚类算法中引入了有效性函数的概念，从而部分克服了模糊C均值聚类算法局部最优和无法确定聚类的类数的问题； - Meanwhile, from the aspect of geometry characteristic of FC-divided in s dimension sample space, a method is proposed for the purpose of getting an effective adjacent radius, adaptive cluster number c and original cluster center of X sample set.
同时，从s维样本空间的F~c-划分几何特性出发，提出了一种求取样本集的类势有效邻域半径和自适应求取聚类数和聚类中心初值的方法； - In clustering analysis, the number of clusters is a very important parameter, and the determination of the optimal cluster number is one of the key points.
在聚类分析中，聚类数是一个非常重要的参数，最佳聚类数的确定问题是聚类分析研究的热点之一。 - Rival Penalized Competitive Learning can cluster and get a proper cluster number automatically.
次胜者受罚竞争学习规则可以进行有效的聚类并自动确定适当的聚类数目。 - So the current question is whether we can confirm the cluster number directly, not using any assumptions.
因此现在的问题是我们能否比较方便地直接确定聚类数，而不需任何假设。 - The improved fuzzy C-means clustering algorithm has better robustness and makes the cluster results insensitive to the predefined cluster number.
改进后的模糊C-均值聚类算法具有更好的鲁棒性，且放松了隶属度条件，使得最终聚类结果对预先确定的聚类数目不敏感。 - The Clustering takes advantage of geographic information of all nodes to adapt its cluster number, and forms the k clusters based on Minimum Spanning Tree and Kruskal Algorithm.
聚类时充分考虑到节点分布的地理信息，自适应地调节聚类的数目，再根据图论中最小生成树的理论，利用Kruskal算法将所有节点划分为k类。 - But, in this aspect, many content work has been done, so the paper will choose a right clustering rule based on the work of them, in order to confirm cluster number directly under no assumptions.
但是，在此方面，人们已经做了很多有意义的工作，所以本文将在前人的基础上选择一个恰当的聚类准则函数，以便在无任何假设条件的前提下比较简单地直接确定聚类数。 - Based on the LEACH routing protocol, we improve the LEACH routing protocol, and then name the advanced routing protocol LEACH NEW, in which we improve cluster head selection algorithm and optimal cluster number determination of LEACH respectively.
在LEACHNEW中，我们分别在簇头选择算法和网络中最优簇数的确定两方面对LEACH进行了改进。 - DECA searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes;
通过改进的遗传策略来优化染色体长度，实现对聚类个数进行全局寻优； - The mixing matrix is firstly estimated by clustering separation of Cy, and then the estimation of sources is made. In this way, the optimal threshold of dissimilarity and the corresponding cluster number are produced automatically.
随后，先通过关于Cy的聚类分离来估计混合矩阵，再根据混合矩阵估计源，其中最佳不相似阈值和相应的聚类数量是自动生成的。 - In the part of "3D Model Segmentation", the vector of Gauss-Mean curvature, that of Max-Min curvature, that of RMS-Absolute curvature are compared through their performances in segmentation. The effect of cluster number is also tested through experiments.
在三维模型分割方面，对高斯-均值曲率向量、最大-最小曲率向量、RMS-绝对曲率向量等三种特征向量在分割中的性能，以及指定聚类数目对分割结果的影响通过试验进行了比较。 - In order to get a sparse network, integrate with the conservative interaction between genes on the various levels of cluster number.
通过在不同聚类数量水平上的建模结果进行综合分析，可以得到具有保守特性的基因间相互作用关系，从而得到一个稀疏的调控网络。 - In the algorithm, each ant represents a data object. It will decide its next moving position according to similarity function and probability converting function between it and its neighbors. At the same time it will update its cluster number according to clustering rules.
在算法中，一个主体蚂蚁代表一个数据对象，根据它与邻域空间中的主体蚂蚁的相似度函数和转换概率函数来确定下一个移动位置，同时依照聚类规则集合动态更新其类号。 - Fourth, improve the calculation method of the preference p according to the need of clustering, then we can control the cluster number.
第四，改进偏好参数p的计算方法，根据聚类需要，控制聚类数。 - On the basis of dynamic clustering described in LEACH, transmission time slot length computing and channel reuse are considered in the proposed scheme. With the convex optimization theory, the joint optimization problem involving cluster number, transmission time allocation and channel reuse distance is solved.
该方案基于LEACH协议的动态分簇思想，结合了传输时隙计算与信道复用等方法，采用凸优化理论，解决了簇数、节点传输时隙分配和信道复用距离间的联合优化问题。 - The clustering, which can determine the cluster number automatically, has very important significance in practice.
自动确定聚类数目的聚类算法，在现实应用中有着很重要的意义。 - The algorithm automatic definite cluster number, also automatic diagnosis lower density point.
算法能自动确定聚类数，还能自动识别低密度点。 - In some cases, it is difficult to obtain the prior knowledge of the target cluster number.
在某些特定情况下，很难获得具体的目标聚簇数。 - CNTC uses the prior knowledge of target cluster number as the stop condition.
CNTC使用先验的目标聚簇数作为终止条件。 - How to determine the optimal cluster number dynamically is discussed, and the factors which influence the optimal cluster number are also analyzed.
对如何动态确定最优簇数目进行了研究，分析了影响最优簇数目的因素。 - After study on the merits and shortcomings of the existing method which is used to find cluster in complex networks, we find that the clustering evaluation function can solve the difficult problem in initial cluster number by constructing a suitable clustering evaluation function.
在研究了现有复杂网络聚类算法的优缺点之后，发现聚类评价函数可以避免初始簇结构数难以抉择的问题，而通过构建合适的聚类评价函数可以解决此问题。 - The purpose of using hierarchical cluster and K-means cluster together, is that provide K-means cluster initial cluster number K from hierarchical cluster.
前人采用层次聚类与K均值聚类结合使用的方法，目的是利用层次法为K均值聚类法提供初始聚类数K。 - However, the traditional spectral clustering algorithm performs not well in dealing with the problems such as self defining parameters, processing the high-throughput data and automatically determining the cluster number.
然而在如何自定义参数、如何处理大规模数据以及如何自动确定最终聚类个数等问题中，传统的谱聚类算法都没有给出很好的解决方法。