Абстрактный

Computer network based on improved neural network fault diagnosis research

Xianhao Miao

Computer network is one of the most important equipment in the whole world, with the gradual and rapid development of its scale, howto manage andmaintain the computer network is becomingmore andmore complicated. The network fault diagnosis has become peopleÂ’s focus. With the development of artificial intelligence, by introducing neural network technology into the area of network fault diagnosis, neural network can bring out its advantages in the fault diagnosis. This article would employ SOMneural network andBP neural network, the sampleswould be clustered by using SOM neural network, and the results of the cluster would be put back into the original samples, whichwould also be setwith certainweights, through the weightsÂ’ consistent updating, the convergence speed of BP neural network can be improved. Through using LMalgorithmto improve BP neural network and using computer network diagnosis as practical samples to simulate and analyze computer, the validity of this method has been proved, and at the same time building a system of computer network diagnosis can be very meaningful for theoretical study and practical use.