摘要
针对话务量的特性,提出了一种基于支持向量机分块回归分析的话务量预测模型,将话务量按日期分为工作日话务量、周末话务量进行建模,采用不同的模型预测相应的话务量。实验结果证明了该模型的有效性,相比传统的ARMA模型获得了更好的预测效果。
According to the characteristics of communication traffic, a traffic forecasting model based on multiple Support Vector Machines （SVM） regression functions was proposed. In this model, the traffic data will be divided into two groups by the date, which are the working-day traffic data and the weekend traffic data. Then two different SVM models are trained using those data. The experimental results show that this model is very effective. Moreover, the performance of this model outperforms that of traditional ARMA model.
出处
《计算机应用》
CSCD
北大核心
2008年第9期2230-2232,2235,共4页
journal of Computer Applications
关键词
话务量分析
预测模型
支持向量机模型
ARMA模型
communication traffic analysis
forecasting model
Support Vector Machines （SVM） model
ARMA model
