Parameters of Network Traffic Prediction Model Jointly Optimized by Genetic Algorithm

In order to improve the performance of network traffic prediction model, a novel network traffic prediction model is proposed in this paper which embedding dimension and time delay of network traffic time series are jointly optimized by genetic algorithm. The optimail embedding dimension and time delay are used to establish the one-step and multi-step based on RBF neural network, finally, the simulation experiments are carried out to test the performance of the proposed model. The results show that the proposed model can select the optimal embedding dimension, delay time, and can significantly improve the prediction accuracy of network traffic, and the prediction resresults is better than reference models.