利用径向基函数神经网络和选择的特征值对缺陷进行分类。
Defects are classified by radial basis function (RBF) network and features selected.
最后,利用径向基函数网络强大的函数逼近功能,识别内燃机气缸压力。
Finally, the cylinder pressure is identified by using radial base function (RBF) network, which is featured with the powerful functional approach.
介绍了利用径向基函数神经网络进行水轮机综合特性曲线数据处理的方法。
The method of data treatment concerning hydroturbine synthetic characteristic curve by radial basis networks is introduced.
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