In this paper, the model structure and the application of Radial Basis Function Neural Network (RBF NN) to fault diagnosis of power transformer is presented.
研究了径向基函数(RBF)神经网络的模型结构及其在电力变压器故障诊断中的实现方法。
Based on the Radial Basis Function neural network, a kind of fault auto-diagnosis system of dam safety monitoring is established.
基于径向基函数神经网络，建立了大坝安全自动化监测的非线性故障自诊断系统。
A new method of synthetic application of neural network technique sorting function and Dempster-Shafer theory (D-S) fusion diagnosis of faults decision-making is researched.
研究了一种综合应用神经网络的分类功能和D S推理融合诊断的故障决策新方法。
The identifying model of time variation was built, on the basis of radial basis function neural network to solve the problem of diagnosis depth.
利用时变基频的求解方法，建立基于径向基函数网络的时变基频识别模型，解决“深度”复杂性问题；
The identifying model of time variation was built, on the basis of radial basis function neural network to solve the problem of diagnosis depth.
利用时变基频的求解方法，建立基于径向基函数网络的时变基频识别模型，解决“深度”复杂性问题；
应用推荐