计算机工程与应用Issue(10)：92-95,100,5.DOI:10.3778/j.issn.1002-8331.1312-0019
基于小波变换的网络流量组合预测模型
Network traffic combination prediction model based on wavelet transform
摘要
Abstract
In order to improve predict accuracy, a combination prediction model of network traffic is proposed based on wavelet decomposition(WA-ARIMA-LSSVM). In view of the network flow multi-scale characteristic, the network traffic time series is decomposed, and then autoregressive moving average models is used to prediction high frequency of for net-work traffic which low frequency is prediction by least squares support vector machine, finally high frequency and low frequency results are reconstructed, and model performance is tested by simulation experiment. The results show that com-pared with other network traffic prediction models, WA-ARIMA-LSSVM can accurately reflect the complex change trends of network traffic and improves the prediction accuracy of network traffic.关键词
网络流量/差分自回归滑动平均/最小二乘向量机/小波变换/组合预测Key words
network traffic/Autoregressive Integrated Moving Average Model(ARIMA)/Least Squares Support Vector Machines(LSSVM)/wavelet transform/combination prediction分类
信息技术与安全科学引用本文复制引用
崔兆顺..基于小波变换的网络流量组合预测模型[J].计算机工程与应用,2014,(10):92-95,100,5.基金项目
甘肃省科技计划资助；甘肃省自然科学研究基金计划（No.1107RJZE252）。 （）
