2) nearest neighbor clustering algorithm
最近邻聚类算法
1.
Forecasting models are established by using radial basis function(RBF) neural network based on nearest neighbor clustering algorithm(NNCA) and autoregressive integrated moving average(ARIMA).
根据基于最近邻聚类算法(NNCA)的径向基(RBF)神经网络和自回归求和滑动平均(AR IMA)两种方法,建立了各自的单项预测子模型,并利用RBF神经网络对两个单项预测子模型结果进行组合预测,得到最终的预测值。
2.
By analyzing nearest neighbor clustering algorithm, a new nearest neighbor clustering algorithm is proposed.
在分析现有最近邻聚类算法所存在问题的基础上,提出了一种先利用均值规格化的思想来确定算法的初始半径,然后根据启发式规则修改聚类半径的新的最近邻聚类算法。
3.
The new algorithm brings in the Nearest Neighbor Clustering Algorithm to initialize the number and center of clustering.
该算法引入了最近邻聚类算法来初始化FCM算法的聚类数和聚类中心。
3) Nearest neighbor-clustering algorithm
最近邻聚类算法
1.
The RBF network based on improved nearest neighbor-clustering algorithm is introduced at first.
应用基于最近邻聚类算法的径向基函数(RBF)网络建立了军用无人机研制费用预测模型,并采用该模型对某型军用无人机研制费用进行了预测。
2.
The nearest neighbor-clustering algorithm has a short training time,less work to calculate and the number of hidden units is not to be determinated in advance in the various RBFNN learning algorithms,the network is optimization after clustering and can be trained on-line,it is an adaptive clustering algorithm for nonlinear real-time system.
在RBF神经网络的各种学习算法中,最近邻聚类算法学习时间短、计算量小,不需要事先确定隐单元的个数,完成聚类所得到的网络是最优的,并且可以在线学习,是一种自适应聚类学习算法,非常适合非线性实时系统的应用。
4) NNC algorithm
最近邻动态聚类
5) nearest neighbor-clustering algorithm
最近邻聚类学习算法
6) nearest neighbor-clustering method
最近邻聚类法
1.
Adopting a hybrid learnging algorithm,which combines the nearest neighbor-clustering method with the gradient descent method,to construct a RBF neural network,the controlled objects can be identified on-line and the parameters of PID master controller can be adjusted on-line.
采用一种最近邻聚类法和梯度下降法相结合的混合学习算法构造RBF神经网络,在线辨识被控对象并对PID主控制器参数进行在线调整。
补充资料：动态
①（事情）变化发展的情况：科技～ㄧ从这些图片里可以看出我国建设的～。②艺术形象表现出的活动神态：画中人物，～各异，栩栩如生。③运动变化状态的或从运动变化状态考察的：～工作点ㄧ～电流ㄧ～分析。
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