1) merger cluster center
归并聚类中心
2) combine the factors of the target
聚类归并
3) Merge clustering centers
合并聚类中心
4) clustering center
聚类中心
1.
New structure algorithm of clustering center and category determination method;
新的聚类中心构造算法及类别判定方法
2.
With the Kohonen network clustering in neural network employed, the degree of relationship of the universal joint axle of the rolling mill was input to Kohonen network as the training sample, studied and clustered by the network to generate different clustering centers according to the different depth and different degree of relationship among the cracks.
由于裂纹深度不同 ,裂纹故障的关联度不同 ,于是网络便产生不同的聚类中心点 。
3.
With the characteristics of the Kohonen network clustering in neural network,the degree of relationship of universal joint axis of rolling mill is input to Kohonen network as training sample,and is studied and clustered by the network to generate different clustering centers owing to the different depth and different degree of relationship among severity of crack.
利用神经网络中Kohonen网络聚类的特点,把小型轧机万向接轴裂纹故障的不同关联度,作为Kohonen网络的训练样本输入到Kohonen网络中去,并由Kohonen网络学习和聚类产生不同的聚类中心点。
5) cluster center
聚类中心
1.
Optimizing initial cluster center of K-means algorithm
优化初始聚类中心的K-means算法
2.
Since each single fault diagnosis method has its advantages and disadvantages,so after the immune system is applied to choosing hidden layer neural network data and getting a cluster center,then a suitable layer weight is selected,and neural network output is calculated,the output result shows that the diagnosis is effective.
近年来,神经网络在故障诊断领域中应用广泛,但任何单一的故障诊断方法都有其优点和缺点,因此将免疫系统应用于神经网络隐层数据中心的选择,训练得出聚类中心,然后选择一种合适的确定隐含层到输出层的权值,计算得出神经网络的输出,并根据输出结果诊断出故障的类型。
3.
The iterative expressions for cluster center and fuzzy membership are deduced respectively.
对K-HarmonicMeans算法进行扩展,考虑到数据点对不同类的隶属关系,将模糊的概念应用到聚类中,提出了模糊K-HarmonicMeans算法,推导出聚类中心和模糊隶属度的迭代公式。
6) center clustering
中心聚类
1.
RBF design method based on center clustering and PSO
采用中心聚类与PSO的RBF网络设计方法
补充资料：归并
①把这个并到那个里头；并入：撤消第三组，把人～到第一组和第二组。②合在一起；归拢：把三笔账～起来，一共是五千五百元。
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