An Improved LS-SVR Ensemble Learning in Internet Traffic Prediction

Abstract:

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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:

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 et al., "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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Price:

$35.00

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