Forecasting international bandwidth capacity using linear and ANN methods

Gary Madden and Joachim Tan

MPRA Paper from University Library of Munich, Germany

Abstract: An artificial neural network (ANN) can improve forecasts through pattern recognition of historical data. This article evaluates the reliability of ANN methods, as opposed to simple extrapolation techniques, to forecast Internet bandwidth index data that is bursty in nature. A simple feedforward ANN model is selected as a nonlinear alternative, as it is flexible enough to model complex linear or nonlinear relationships without any prior assumptions about the data generating process. These data are virtually white noise and provides a challenge to forecasters. Using standard forecast error statistics, the ANN and the simple exponential smoothing model provide modestly better forecasts than other extrapolation methods

Keywords: Forecasting; international bandwidth capacity (search for similar items in EconPapers)
JEL-codes: L96 (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (5)

Published in Applied Economics 40 (2008): pp. 1775-1787

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Journal Article: Forecasting international bandwidth capacity using linear and ANN methods (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:13005

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