Network traffic prediction based on parameters joint estimation of phase space reconstruction

摘要

In order to improve the prediction accuracy of network traffic, a network traffic prediction method is proposed based on parameters joint estimation of phase space reconstruction. Extreme learning machine is used as the network traffic prediction algorithm, and the optimal parameters of phase space reconstruction is selected according to prediction results of the network traffic, the simulation analysis is carried out on network traffic data to tested the performance of single step and multi-step prediction model. The results show that the proposed method can effectively select t parameters of phase space reconstruction, significantly improve the prediction accuracy of network traffic, the prediction results is significantly higher than other prediction models.