An Improved LS-SVR Ensemble Learning in Internet Traffic Prediction

摘要：

　　In this paper,we present a new method for internet traffic forecasting based on a boosting LS-SVR algorithm.AdaBoost has been proved to be an effective method for improving the performance of weak learning algorithms and widely applied to classification problems.Inspired by it,we use LS-SVR to complete the initial training; and pay more attention on the high error areasin the time series; then,we use an ensemble learning algorithm to learn these areas.

关键词： Ensemble learning AdaBoost LS-SVR Support Vector Machines

作者: Kunlun Li Yinghui Ma Yongmei Tian Jing Xie

作者单位: College of Electronic and Electrical Engineering, Hebei UniversityBaoding, 071002, China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 3794-3798

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）