The network traffic is the important parameter that measures the burden of network movement and network appearance. It also plays an important role in network layout, traffic management. In traffic management, traffic model is used to evaluate the mechanism of join control and predict network performance. The grey model and neural network have good effect in reflecting the variable trend of data. With the development of grey neural network theory and its widely used, many improved and new generation methods have been proposed. On the research of neural network ,this paper add a compensated error, so the prediction value equals to the output value of grey neural network model plus the compensated error signal. The simulation results show that the integrated model can improve the prediction precision obviously compared to the other algorithm.
['Feng Wang', 'Hongbin Xia']
Network Traffic Prediction Based on Grey Neural Network Integrated Model