Meanwhile optimization theory based HCM clustering algorithm is used to cluster sample data to determine the number of node of hidden layer, so that the efficiency of RBF network in use is high.
同时采用基于优化原理的HCM算法实现聚类过程，来确定R BF网络的隐含层节点数，使网络的利用效率较高。
The output of each input layer node is fed to each of six hidden-layer nodes, which in turn feed three output nodes.
再将各个输入层节点的输出 提供给 6 个隐藏层节点，这些隐藏层节点将依次提供给 3 个输出接点。
Aiming at the slow convergence rate of BP neural network, append a correlative node on hidden layer, improve the adaptive ability and rate of studying of neural network.
针对BP算法收敛速度慢的特点，在隐含层上加入了关联节点，改善了网络的学习速率和适应能力。
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