1)K-meansK均值
1.PSO-based K-means Algorithm and Its Application;基于粒群优化的K均值算法及其应用
2.Application of improved k-means clustering algorithm in intrusion detection;改进k均值算法在网络入侵检测中的应用研究
3.A Research of Genetic K-Means Algorithm Based on Variable Length Encoding;一种基于变长编码的遗传K均值算法研究
英文短句/例句
1.K Mean Cluster Algorithm with Refined Initial Center PointK均值聚类算法初始质心选择的改进
2.Updated Learning Algorithm of Support Vector Data Description Based on K-Means Clustering改进的基于K均值聚类的SVDD学习算法
3.Random network topology model based on K-means基于K均值聚类的随机网络拓扑模型
4.K-means method/median filter algorithm and recursive realizationK均值和中值滤波混合算法及其递归实现
5.A Research of Genetic K-Means Algorithm Based on Variable Length Encoding;一种基于变长编码的遗传K均值算法研究
6.K-means Clustering Method Based on Mixture of Genetic Operator and Partical Swarm基于遗传算子和粒子群混合的K均值聚类方法
7.IMPROVED K-MEANS CLUSTERING FOR REMOTE SENSING IMAGES IN COMBINATION OF COLOUR AND TEXTURE结合颜色和纹理的改进K均值遥感图像聚类
8.The Two-stage Text Clustering Algorithm Based on K-mesans and aiNet基于K均值和aiNet的两阶段文本聚类算法
9.Partial K-Means Algorithm Based on Spatial Context Information基于空间上下文信息的部分K均值算法
10.Application of K-means Algorithm on PSO in Telecom Customer Segmentation粒子群的K均值算法在电信客户细分中的应用
11.K-NN, K-means and the Application in Text Mining;K-近邻、K-均值及其在文本分类中的应用
12.K-Means-Based Fuzzy Classifier Design;基于K-均值算法的模糊分类器设计
13.Dynamic Spectrum Access Technical Based on K-means Clustering基于K-均值聚类的动态频谱接入技术
14.Application of k-means clustering analysis in process improvementk均值聚类分析在过程改进中的应用
15.Segmentation Algorithm for Green Apples Recognition Based on K-means Algorithm基于K-均值聚类的绿色苹果识别技术
16.An improved genetic K-means clustering algorithm based on image segmentation改进的图像分割遗传K-均值聚类算法
17.Application of k-means algorithm in intrusion detection Systemk均值算法在网络入侵检测中的应用
18.Improved K-Means Clustering Algorithm Based on SOFM基于SOFM网络的改进K-均值聚类算法
相关短句/例句
K-means algorithmK-均值法
3)k-meansK-均值
1.K-means Clustering Algorithm Based on Self-Adoptively Selected Density Radius;基于密度半径自适应选择的K-均值聚类算法
2.Application of K-means algorithm in relational database;K-均值聚类算法在关系数据库中的应用
3.Image Segmentation Based-on an Improved K-Means Clustering Algorithm;基于改进的K-均值聚类图像分割算法
4)K-meanK-均值
1."K-mean unsupervised method" was used to classify the two vegetation indices,NDVI and EVI,of the studied area.从MODIS影像中划出一块无云区域作为研究对象,求出该研究区的NDVI和EVI,运用K-均值分类法分别对2种植被指数进行非监督分类。
2.K-mean methods are usually sensitive to initial clustering c.K-均值算法受初始聚类中心的选择影响较大,对于不规则分布的样本往往聚类的效果不佳。
5)Uniform K Value均质K值
6)k-th mean valuek次均值
1.On a note on k-th mean value of cubic complements;关于立方幂补数k次均值的注记
延伸阅读
均值不等式几个重要不等式(一)一、平均值不等式设a1,a2,…, an是n个正实数，则，当且仅当a1=a2=…=an时取等号1.二维平均值不等式的变形(1)对实数a,b有a2+b2³2ab (2)对正实数a,b有(3)对b>0，有， (4)对ab2>0有，(5)对实数a,b有a(a-b)³b(a-b) (6)对a>0,有(7) 对a>0,有 (8)对实数a，b有a2³2ab-b2(9) 对实数a，b及l¹0，有二、例题选讲例1.证明柯西不等式证明：法一、若或命题显然成立，对¹0且¹0，取代入(9)得有两边平方得法二、，即二次式不等式恒成立则判别式例2.已知a>0,b>0,c>0,abc=1,试证明：(1)(2)证明：(1)左=[]=³(2)由知同理：相加得：左³例3.求证：证明：法一、取，有a1(a1-b)³b(a1-b), a2(a2-b)³b(a2-b),…, an(an-b)³b(an-b)相加得(a12+ a22+…+ an2)-( a1+ a2+…+ an)b³b[(a1+ a2+…+ an)-nb]³0所以法二、由柯西不等式得： (a1+ a2+…+ an)2=((a1×1+ a2×1+…+ an×1)2£(a12+ a22+…+ an2)(12+12+…+12)=(a12+ a22+…+ an2)n,所以原不等式成立例4.已知a1, a2,…,an是正实数，且a1+ a2+…+ an<1，证明：证明：设1-(a1+ a2+…+ an)=an+1>0,则原不等式即nn+1a1a2…an+1£(1-a1)(1-a2)…(1-an)1-a1=a2+a3+…+an+1³n1-a2=a1+a3+…+an+1³n…………………………………………1-an+1=a1+a1+…+an³n相乘得(1-a1)(1-a2)…(1-an)³nn+1例5.对于正整数n，求证：证明：法一、>法二、左==例6.已知a1,a2,a3,…,an为正数，且，求证：(1)(2)证明：(1)相乘左边³=(n2+1)n证明(2)左边= -n+2(= -n+2×[(2-a1)+(2-a2)+…+(2-an)](³ -n+2×n
