A novel hybrid intelligent fault diagnosis method based on improved RBF neural network
作者： Yi Liu
关键词:
摘要: liuyi2396@163.com Abstract. The radial basis function neural network (RBFNN) is a great potential artificial intelligence technology and can effectively realize the fault diagnosis for small sample nonlinear problem. But parameters of RBFNN model seriously affects generalization ability accuracy on extent. So an improved differential evolution algorithm based dynamic adaptive adjustment strategy proposed to optimize obtaining optimal RBFNN(DASDERBFNN) method. Then DASDERBFNN method used construct new (DSDRBFNFD) experiment results show that DSDRBFNFD obtain higher effective engine.
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