First, determining the initial system by the method of subtractive clustering. Second, learning the system.
首先，通过减法聚类来确定初始系统，然后再进行学习训练。
A new method of subtractive clustering RBF network for air condition breeze fan fault diagnosis is presented.
提出了一种减聚类径向基函数神经网络的纺织空调送风风机故障诊断方法。
The application of Subtractive Clustering Fuzzy Inference System model to forecast short-term load is presented.
采用减法聚类辅助模糊推理系统进行电力系统短期负荷预测。
On the basis of analyzing RBPNN in theory, subtractive clustering is used to determine its hidden centric vector.
在对径向基概率神经网络进行理论分析基础上，采用减法聚类方法确定它的隐中心矢量。
A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure.
在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，使网络结构得到优化。
A learning algorithm of subtractive clustering method for RBFNN is used to obtain the parameters of radial basis function, so that RBFNN has an optimized structure.
在RBF神经网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，从而使神经网络结构得到优化。
In this method, subtractive clustering was adopted to divide the input space into several sub-spaces, and sub-models were built by Least Square SVM (ls SVM) in every sub-space.
该建模方法通过减聚类方法将输入空间划分为一些小的局部空间，在每个局部空间中用最小二乘支持向量机(LS -SVM)建立子模型。
In this method, subtractive clustering was adopted to divide the input space into several sub-spaces, and sub-models were built by Least Square SVM (ls SVM) in every sub-space.
该建模方法通过减聚类方法将输入空间划分为一些小的局部空间，在每个局部空间中用最小二乘支持向量机(LS -SVM)建立子模型。
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