基于小波分析和神经网络的网络流量预测

摘要

网络流量的准确预测对于提高网络服务质量与网络安全有很重要的作用.本文主要对流量序列进行小波分解和重构,并结合神经网络对网络流量进行预测,新的算法可以有效提高预测精度.通过分析神经网络及非线性预测模型的优劣,建立一个网络流量预测模型.同时利用实际采集的网络流量数据对模型进行仿真,证实该模型可以有效控制由各种因素导致的误差,从而提高网络流量的预测精度.%Accurate forecasts for network traffic was very important in improving network service quality and network security. This paper mainly studied on wavelet decomposition and reconstruction of the flow series, combined with neural network to predict the network traffic. The new algorithm could enhance the prediction of forecasting effectively. By analysising the advantages and disadvantages of neural network and nonlinear models, a network traffic prediction model was established.The model was stimulated by using the actual collected network traffic data. The results indicated that the model could effectively control errors caused by various factors and improve the prediction accuracy of network traffic.