Computer Network Fault Diagnosis Based On Neural Network

Computer network is one of the world's most important infrastructures in twenty-first Century, network fault diagnosis has become the focus of attention. With the development of artificial intelligence, using the neural network technology into the network fault diagnosis area can play an important role to the advantages of neural network in fault diagnosis. In this paper, the method is widely used, which is combined the self organizing feature map (SOM) neural network and multilayer feedforward neural network (BP): The result of the training samples using SOM neural network clustering algorithm is added to the original training samples and set a certain weight, through iterative update to the weight, in order to improve the convergence the speed of BP neural network. Using computer network fault diagnosis as a practical example for the computer simulation and analysis developes a set of computer network diagnosis system can provide reference and assistance for the work of theory research and application.