1) fuzzy c linear clustering
模糊c-线性簇聚类
2) possibilistic fuzzy c-means clustering
可能性模糊C-均值聚类
1.
Based on combination of FCM and PCM,possibilistic fuzzy c-means clustering(PFCM) overcomes these shortcomings.
可能性模糊C-均值聚类(PFCM)综合了FCM和PCM算法并且克服了这些缺点。
3) fuzzy c-means clustering
模糊C均值聚类
1.
The analog circuits fault diagnosis based on fuzzy C-means clustering;
基于模糊C均值聚类的模拟电路故障诊断
2.
Segmentation of fat and lean meat in beef images based on fuzzy C-means clustering;
基于模糊C均值聚类的牛肉图像中脂肪和肌肉区域分割技术
3.
Brain MR image segmentation based on anisotropic Gibbs random field and fuzzy C-means clustering model;
基于Gibbs场与模糊C均值聚类的脑MR图像分割
4) fuzzy C-means clustering
模糊C-均值聚类
1.
Escaped toll analysis of ETC system customer data based on fuzzy C-means clustering;
基于模糊C-均值聚类的ETC系统客户的逃费分析研究
2.
In order to recognize the pollutant sources and build the correspondence relationships between contaminated sources and important pollutants,a set of intelligent recognizing method based on correspondence factor analysis and fuzzy C-means clustering(short for IRM-CFA&FCM) is developed.
为识别东湖污染物来源,建立排污口与主要致污因子之间的对应关系,提出了污染物来源智能识别方法;该方法巧妙耦合了对应分析、模糊C-均值聚类及聚类有效性函数等方法,并用加速遗传算法有效解决了这一复杂问题。
3.
To improve the accuracy of text clustering,fuzzy c-means clustering based on topic concept sub-space(TCS2FCM) is introduced for classifying texts.
为了改善文本聚类的准确度,提出用基于主题概念子空间的模糊c-均值聚类(TCS2FCM)方法来分类文本。
5) FCM
模糊C均值聚类
1.
A novel algorithm for discretization of continuous attributes in rough set theory based on FCM;
基于模糊C均值聚类的粗集理论连续属性的离散化新算法
2.
Based on the idea of combining models to improve prediction accuracy and robustness, the soft sensor model of the dry point of the first top naphtha is built by using FCM to divide a whole training dataset into several clusters with different centers.
应用多神经网络建立初顶石脑油干点软测量模型,首先采用模糊C均值聚类法将样本集分成具有不同聚类中心的子集,每个子集运用BP神经网络训练得出子模型,然后根据聚类后产生的隶属度将各子模型的输出加权求和获得初顶石脑油干点软测量值。
3.
With only pixel value information taken into account and non-robust Euclidean distance used as the distance measure standard, the classical Fuzzy C-means Clustering (FCM) algorithm lacks enough robustness in the image segmentation.
传统模糊C均值聚类(FCM)算法进行图像分割时仅利用了像素的灰度信息,并且使用对噪声较敏感的欧氏距离作为像素与聚类中心距离度量的标准,因此抗噪性能较差。
6) fuzzy C-means
模糊C均值聚类
1.
A new strategy for speaker recognition,triple-particle fuzzy C-means clustering(FCM),called TP-FCM,was proposed.
基于粒子群优化(particle swarm optim ization,PSO)提出一种说话人识别算法—三粒子模糊C均值聚类算法。
2.
The new algorithm is based on the principle of fuzzy C-means(FCM) clustering algorithm and the transiently chaotic neural network(TCNN) algorithm.
带容量约束的多车调度问题是典型的NP-hard问题,利用模糊C均值聚类算法的相似性分类原理及混沌神经网络的全局搜索能力和高搜索效率,提出了一种快速且易于实现的新的混合启发式算法。
3.
An algorithm on data association for multisensor multitarget tracking (MSMTT) based on fuzzy comparability and fuzzy C-means (FCM)is proposed.
利用模糊相似性和模糊C均值聚类算法相结合,提出一种求解多传感器多目标跟踪数据关联问题的方法。
补充资料：线性簇
线性簇
linear variety
线性簇tlil.ar，州旬;JlllHe‘“oe MHO，o6pa3He]，毕性流形抽noirmadfo】d)，仿射子空间(affix丈su比pace). (线性)向且空间(vector sPaee)E中的子集M且是E中线性子空间(五班沮rs幽p以沁)L的平移，即形如x。十L的集合M，其中x。任M.集合M唯一确定L，而x。只是模L确定的: xo+L=xt+N，当且仅当L=N及x，一x。〔L.M的维数是L的维数.与余维数为1的子空间相对应的线性簇称为超平面(h只姆rplane).M .H .Bd自万ex“cK滋撰葛显良译
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条