作　　者： ; ; ; ; ;

机构地区： 重庆三峡学院电子与信息工程学院电子工程系

出　　处： 《计算机工程与设计》 2006年第8期1341-1342,1345,共3页

摘　　要： 给出了网络流量短期预测方法。该方法运用小波变换自适应时频局部化分析方法和改进的Mallat算法将网络流量分解到不同频带上,然后对各子频带上的小波分进行不同阈值的消噪处理,再对仍是非平稳过程的分量进行差分处理使其转化为平稳序列,最后对各平稳过程分量采用ARMA模型进行预测。实际流量分析表明该方法简便,且短期预测精度较高。 Method of network traffic short-term forecasting is presented. The network traffic is decomposed into different frequency bands by using method of analyzing the self-adaptive time-frequency localization of wavelet transform, and the improved Mallat algorithm. And then, via different thresholds, wavelet weights in different frequency bands are denoised. After that, wavelet weights still in unstable sequences are transformed into stable sequences by carrying on difference disposal. Finally, the ARMA model is taken to predict the weights of all stable sequences. Practice of network traffic analysis shows that the method is simple, applicable and has high accuracy for short-term prediction.

关 键 词： 网络流量 小波分析 算法 模型 预测

领　　域： [自动化与计算机技术] [自动化与计算机技术]