聚类

Genetic distance between Guizhou White Buffalo and Zunyi Buffalo is the closest (0.0910). The clustering dendrograph drawn by UPGMA can clearly reflect the geography distribution, the feature of genetic differentiation, and genetic relationships among Guizhou White Buffalo and 6 buffalo populations.

由UPGMA聚类法得到的系统聚类图反映了贵州白水牛和6个普通水牛群体的亲缘关系远近程度，贵州白水牛没有单独聚为一类，而是与同分布区的遵义普通水牛首先聚类，然后依次与其余地区的普通水牛聚类。

Firstly, 112 symptoms of asthenia syndrome which frequency greater than or equal to 10% were clustered and recognized. Secondly, every group cases of asthenia syndrome after first stage clustering were clustered and recognized again to get corresponding sthenia syndrome. Thirdly, we searched for the distribution laws between the clustering result and the data of demography to get the distribution laws of every group characteristic symptoms corresponding asthenia syndrome, of sthenia syndrome corresponding every group asthenia syndrome.

首先根据频率大于10%的112个虚证症状进行聚类识别，再对聚类结果中每组虚证病例进行兼夹实证聚类识别，并对聚类识别结果与性别、年龄等人口学特征之间分布规律进行探索，从而得出每类虚证对应的特征症状分布规律及程度，虚证证候对应的兼夹实证分布规律，以及各类主次证候间辨证关系及发展趋势，及其与性别、年龄等人口学特征的分布规律。

A new hybrid clustering algorithm in phase of highefficiency and good quality was put forward on the foundation of synthetically analyzing Kmeans clustering algorithm based on partition and agglomerative clustering algorithm based on hierarchy, and consulting some improved hybrid clustering algorithms.

在综合分析基于划分的K均值聚类算法和基于层次的凝聚聚类算法的基础上，借鉴各种混合聚类方法，提出了一种执行效率更高和聚类质量更好的分阶段混合聚类算法。

The results show that,the kernelized versions of the Xie-Beni index VXB and its emendatory index VK are the most effective and reliable of the indices considered,so can be given the priority as the cluster validity criteria for KFCM algorithm.

将经典的聚类算法推广到核Hilbert空间，是无监督学习领域近年来的研究热点之一[1~6]。然而，和原空间中的聚类算法一样，核化的聚类算法也需要事先给定聚类数目c，这直接影响了这些算法的易用程度和实际性能。众所周知，聚

Result: Clustering analysis showed that clustering relations were far among different Gryllotalpa species and close among the same species from different regions,and there were close relations among the same species from near regions and between Teleogryllus emmus and G. orientalis .

结果 ：聚类分析表明不同的蝼蛄种间聚类关系较远；虽异地但为同一种的蝼蛄聚类关系较近；相近地理位置所产蝼蛄，其聚类关系较近；混乱品种蟋蟀和东方蝼蛄的聚类关系较近。

For contrast experiments, k-means and DBSCAN algorithms are also implemented using Visual C++ 6. 0. We conducted a series of experiments, including the experiment of the correctness of clustering and outlier detection, the experiment of the precision of clustering and outlier detection. The experiment of the runtime, the experiment of the effect of clustering and outlier detection on parameters, the experiment of the impact of clustering and outlier detection precision by the order of data input, and the experiment of the effect of the algorithm validness by the density character of dataset.

本文使用Visual C++ 6.0实现了基于距离的聚类和孤立点检测算法、k-means算法和DBSCAN算法，做了大量的对比实验，包括聚类算法和孤立点检测正确性实验；聚类算法和孤立点检测精度实验；算法执行时间实验；参数对聚类和孤立点检测结果的影响实验；数据输入顺序对算法聚类和孤立点精度的影响实验；数据集密度对算法有效性的影响等。

On the basis of PCA and Fuzzy C-Means Clustering, a new algorithm which can be applied to segment the color image with shadows and faculae is proposed.

论文首先分析了为什么要使用模糊聚类的技术；然后讨论了聚类空间对聚类结果的影响，着重介绍了本文聚类时所用的&指定分割区域色彩特征空间&，分析了采用该空间的理论和实验依据；为了进一步提高分割准确性，根据主分量分析的统计原理，我们进一步对聚类数据进行了权重变换，并在FCM中引入簇分布方向性的计算。

Firstly,the author analyzes principles and general methods of lustering- based Data mining.

本文作者首先认真研究分析了基于聚类的数据挖掘的基本原理，提出了一个将单亲遗传算法与Kohonen聚类算法相结合的混合聚类算法，克服了Kohonen 算法的局部最优问题以及采用普通遗传算法聚类时的搜索速度和聚类精度的矛盾。

In this paper,an automatic sublingual venae extraction method based on K-means clustering was proposed.

舌下络脉诊是中医舌诊中十分重要的一种手段，本研究提出了一种基于特征聚类分析的舌下络脉自动提取方法，该算法在L*a*b*色彩空间下，利用K-均值聚类算法对舌下区域按颜色进行聚类，根据聚类中心的位置，确定舌下络脉所在的聚类，并计算出舌下络脉的特征参数，对每一例舌下数据给出6个参数，表征络脉的长度，宽度以及颜色。

An automatic algorithm was used in the analysis to identify clusters of groupings of patients. We used the classical unsupervised clustering method called the Iterative Self-organizing analysis technique of DATA analysis originally introduced by Ball and Hall.25 The technique allows the splitting and merging of clusters while trying to find the "best" configuration. It therefore, requires very little a priori knowledge about the data and predefining the possible number of clusters or groups is not required. The range of possible minimum and maximum number of clusters within which the algorithm can search for an optimal configuration was determined by a procedure called the chainmap which reorders the multidimensional data in the form of a 2D distance map.26 A patient vector is randomly selected and its nearest neighbor is identified as that with the shortest distance between the 2 patients' vectors.

使用自动算法来分析鉴别患者组的聚类，我们使用经典的最初由Ball和Hall提出的的非监控聚类方法，该技术允许在寻找&最佳&形态使对聚类进行拆分和组合，他不需要对数据专门的知识和对聚类或群的可能数量进行预设，在聚类可能的最大和最小范围内，算法可以通过一个叫Chainmap的程序寻找最理想的形态，该程序记录了来自2D距离图的多维数据。

Since historical times,England ,where the early inhabitants were Celts, has been conquered three times .

从有历史以来，英国，在此地早期居住的是凯尔特人，已经被征服了三次。

Bluetooth OBEX File Transfer Enables the sending and receiving of files on your phone via Bluetooth.

蓝牙OBEX文件移动允许经过蓝牙传送和接受文件。。。。