Network traffic combination prediction model based on wavelet packet analysis is proposed.The original discrete series consisting of network traffic data is decomposed into several approximate series and detail series.Then these series were reconstructed into several low frequency and high frequency series by wavelet packet.These series were predicted by LMMSE and AR models respectively according to their different features.The prediction of the original series can be obtained by the synthesis of each reconstructed series＇ prediction result.The simulation results with the real traffic traces show the accuracy and efficiency of the model.%提出一个基于小波包分析的网络流量组合预测模型,将流量数据构成的原始序列进行小波包分解,并将分解得到的各近似部分和各细节部分分别单支重构成低频序列和高频序列.根据低频序列和高频序列的不同特性,分别采用自回归模型（AR）和线性最小均方误差估计（LMMSE）对未来网络流量进行预测,最后重新组合生成预测流量.通过对真实网络流量的仿真实验,结果显示该模型能够对网络流量进行比较精确的预测.
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