Forecasting international bandwidth capacity using linear and ANN methods
AbstractAn 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
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 13005.
Date of creation: 2008
Date of revision:
Forecasting; international bandwidth capacity;
Other versions of this item:
- Gary Madden & Joachim Tan, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," Applied Economics, Taylor and Francis Journals, vol. 40(14), pages 1775-1787.
- L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
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