基于粗糙径向基神经网络的电网故障诊断新模型

A new fault diagnosis model of electric power grid based on rough radical basis function neural networks

在一种属性约简方法的基础上,利用粗糙集和径向基网络的优势,将二者充分融合,构建了一种电网故障诊断新模型,并对其进行了改造。通过对电网故障诊断算例的仿真实验比较表明,该模型减少了识别的主观因素,简化了网络结构,并且识别效果明显,分类能力强,具有很强的容错性和解释性,有很广阔的应用前景。

On the basis of giving a new type of attribute reduction method, a coupling recognition model is established which combines rough set and neural network closely and rebuilt in this paper. The simulation results illustrate that the model reduces subject factors in signal recognition and improves network＇s structure, and its recognizing effects are obvious and its classifying ability is strong, as well as the model is very error permissible and explicable. It has very wide foreground.