Application of BP Neural Network in Network Fault Diagnosis

Abstract

There are various deficiencies in network fault diagnosis methods but the need for fault diagnosis is further increasing. In order to adapt to the current development needs, the paper applies the artificial neural network concept to network fault diagnosis. Aiming at the slow convergence speed of traditional neural networks and the tendency to fall into the local optimal solution, first we attempt to add the momentum factor and then adopt rough set preprocessing data. The simulation results show that the improved algorithm has a certain advantages for the original BP algorithm, and it has a certain value for future fault diagnosis research.