关键词: 网络流量预测, 提升小波降噪, 最小二乘支持向量机, 在线算法

Abstract: Concerning the problem that the network traffic data has been polluted by noise so that accurate modeling and predicting cannot be achieved, an integrated network traffic online predicting method based on lifting wavelet de-noising and online Least Squares Support Vector Machines (LSSVM) was proposed. First, the Lifting Wavelet De-noising (LWD) was used to pre-process network traffic data, then the phase space reconstruction theory was introduced to calculate the delay time and embedded dimension. On this basis, the training samples were formed and the online LSSVM prediction model was constructed to predict the network traffic. The experimental results show that this prediction model can eliminate the noise effectively and predict the network traffic.

Key words: network traffic prediction, Lifting Wavelet De-noising (LWD), Least Squares Support Vector Machine (LSSVM), online algorithm