k均值算法,k-means英语短句,例句大全

k均值算法,k-means
1)k-meansk均值算法
1.Against the defect of k-means,a new algorithm called KDM is proposed based on k-means and DIANA.针对k均值算法局限于k值和初始中心点选取的情况,提出了一种基于k均值的自动获得k值的KDM算法。
2.K-means algorithm has some deficiencies.K均值算法的聚类个数K需指定,聚类结果与数据输入顺序相关,而且易受孤立点影响。
3.An improved k-means algorithm is applied to cluster the antibody and antigen in IDS, the new IDS has the quite high detection performance.运用K均值算法对人工免疫系统中的抗原和抗体进行聚类,并对该算法进行了适当的改进。

英文短句/例句

1.Application of k-means algorithm in intrusion detection Systemk均值算法在网络入侵检测中的应用
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.K-Means-Based Fuzzy Classifier Design;基于K-均值算法的模糊分类器设计
4.K Mean Cluster Algorithm with Refined Initial Center PointK均值聚类算法初始质心选择的改进
5.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
6.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
7.Improved K-Means Clustering Algorithm Based on SOFM基于SOFM网络的改进K-均值聚类算法
8.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
9.Agriculture Extra-green Image Segmentation Based on Particle Swarm Optimization and K-means Clustering基于PSO与K-均值算法的农业超绿图像分割方法
10.Research on Problems Related to the Initial Center Selection in K-means Clustering Algorithm;K-均值聚类算法初始中心选取相关问题的研究
11.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
12.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
13.A Fuzzy K-Means Customer Clustering Algorithm Combined with PSOA一种结合PSOA的模糊K-均值客户聚类算法
14.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
15.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
16.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
17.K-mean algorithm for optimizing the number of clusters based on particle swarm optimization基于微粒群优化聚类数目的K-均值算法
18.KERNEL FUNCTION FROM THE K-MEANS CLUSTERING FOR NETWORK INTRUSION DETECTION核函数距离K-均值聚类的网络入侵检测算法

相关短句/例句

K-means algorithmk-均值算法
1.The fuzzy clasifier based on the K-means algorithm is ef fi ciently design so that the training patters can be correctly classified.基于K-均值算法的模糊分类器具有很好的分类效果 ,用它可以很准确的对训练样本进行分类。
2.For increasing classifier s classification rate,We make use of the fuzzy theories to K-means algorithm again.为了提高分类器的分类率,再一次把模糊的思想引入K-均值算法,构成双重模糊K-均值算法的分类器,所不同的是把模糊化思想引入到分类规则上;用这样一个模糊规则来表示分类的模糊系统,更加有效地构建了一个能够对训练样本比较准确分类的模糊分类器,用这种方法设计的分类器有效地提高了分类器的分类率;最后用Iris数据进行仿真测试,测试结果显示其分类率能够达到98%左右,并且不需要预定义参数,训练时间短,方法简单。
3.An improved K-means clustering algorithm is proposed,which is based on basic K-means Algorithm,and which choose original clustering centers based on densities and improves clustering effects according to feature weight learning.本文提出了一种改进的K-均值聚类算法,在基本K-均值算法的基础上运用基于密度选择初始中心点并且通过学习特征权值改进聚类效果,克服了基本K-均值算法初始中心点难以确定、聚类结果不稳定的缺点;然后建立了一种基于改进的K-均值算法的人事管理系统聚类分析模型,本模型采用SQL Server 2000数据库实现并成功运用于国内一家知名软件企业的人力资源管理系统中,为该企业选聘人才和用好人才提供了有益的参考。
3)K-meansK-均值算法
1.A New Approach to Ascertain the Initial Clustering Centers of K-means;一种新的确定K-均值算法初始聚类中心的方法
2.A digital image watermarking based on K-means algorithm;基于K-均值算法的数字图像水印技术
3.Clustering algorithms are the typical algo-rithms in the data mining, the K-means algorithm is the most basic algorithm, which has produced many classics and highly effective algorithms.聚类是数据挖掘中的典型算法,其中的K-均值算法是最基本的算法,由该算法产生了许多经典而高效的算法。
4)K-means algorithmK均值算法
1.Traditional K-Means algorithm is sensitive to the initial centers and easy to get stuck at locally optimal value.传统K均值算法对初始聚类中心敏感,聚类结果随不同的初始输入而波动,容易陷入局部最优值。
2.In this paper a new segmentation method is proposed,in which K-means algorithm is combined with mutual information (MI) technique.为了提高分割效果,从分割图像与原图像的内在联系出发,提出了一种新的基于K均值算法与互信息量(mutual information,MI)技术相结合的分割算法。
3.Based on the k-means algorithm, we proposed the PSO-k-means algorithm combining the k-means with PSO.在k均值算法基础上,提出一种将粒子群算法与k均值算法相结合产生基于粒子群的k均值算法(PSO-k均值算法)。
5)fuzzy K-means algorithm模糊K均值算法
1.Data mining model based on improved fuzzy k-means algorithm and neural network algorithm;基于改进模糊k均值算法和神经网络算法的数据挖掘模型
2.Data recorded with a camera network is clustered hierarchically using fuzzy K-means algorithm based on spatial and temporal information respectively,and the quality of each clustering results is evaluated by the tightness and separation criterion(TSC).算法首先通过非重叠多摄像头采集人在环境中不同地点间的运动轨迹;其次,应用两层模糊K均值算法分别对这些运动轨迹进行空间和时间序列上的分类,并利用TSC标准对每一次分类结果进行评估;然后建立每一聚类运动模式的概率方程,依此实现对摄像头网络观测下人运动行为的预测,进而调整机器人的导航策略以达到与人和谐共处的导航目的。
6)K-Means clustering algorithmK-均值聚类算法
1.The learning of this method is divided into two processes,state space learning using K-means clustering algorithm for adaptive discretization of continuous states and policy learning using Sarsa algorithm for finding optimal policy.该方法的学习过程分为两部分:对连续状态空间进行自适应离散化的状态空间学习,使用K-均值聚类算法;寻找最优策略的策略学习,使用替代合适迹Sarsa学习算法。