Paper Title:
An Improved LS-SVR Ensemble Learning in Internet Traffic Prediction
  Abstract

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 areas” in the time series; then, we use an ensemble learning algorithm to learn these areas.

  Info
Periodical
Chapter
Chapter 7: Computer Application in Design and Manufacturing (1)
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
3794-3798
DOI
10.4028/www.scientific.net/AMM.121-126.3794
Citation
K. L. Li, Y. H. Ma, Y. M. Tian, J. Xie, "An Improved LS-SVR Ensemble Learning in Internet Traffic Prediction", Applied Mechanics and Materials, Vols. 121-126, pp. 3794-3798, 2012
Online since
October 2011
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