组合神经网络的网络流量预测研究

Network Traffic Prediction Based on Combination Neural Network

提出一种组合神经网络的网络流量预测模型.首先采用SMOF网络对网络流量数据进行聚类,然后采用Elman网络对聚类后的流量数据进行训练并预测,同时采用遗传算法对Elman网络的网络结构进行优化,提高网络流量预测精度.仿真结果表明,组合神经网络加快了网络流量预测速度,提高了网络流量预测精度,克服了单一预测模型不足,为网络流量预测提供了新的思路,具有很好的应用前景.

This paper proposes a combination network traffic prediction model based on neural networks.Firstly,SMOF network is used to cluster the network traffic data,and then used the clustering Elman network to train and predict,and Elman network is optimized by genetic algorithm to improve the network traffic prediction accuracy.Simulation results indicate that the combined neural network prediction model accelerates the prediction speed and improve the network traffic prediction accuracy,overcoming the single forecasting model insufficient,it has the very good application prospects.