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Long-term sales forecasting using holt-winters and neural network methods

Kotsialos, Apostolos; Papageorgiou, Markos; Poulimenos, Antonios

Authors

Apostolos Kotsialos

Markos Papageorgiou

Antonios Poulimenos



Abstract

The problem of medium to long-term sales forecasting raises a number of requirements that must be suitably addressed in the design of the employed forecasting methods. These include long forecasting horizons (up to 52 periods ahead), a high number of quantities to be forecasted, which limits the possibility of human intervention, frequent introduction of new articles (for which no past sales are available for parameter calibration) and withdrawal of running articles. The problem has been tackled by use of a damped-trend Holt–Winters method as well as feedforward multilayer neural networks (FMNNs) applied to sales data from two German companies.

Citation

Kotsialos, A., Papageorgiou, M., & Poulimenos, A. (2005). Long-term sales forecasting using holt-winters and neural network methods. Journal of Forecasting, 24(5), 353-368. https://doi.org/10.1002/for.943

Journal Article Type Article
Publication Date 2005-08
Deposit Date Feb 26, 2008
Journal Journal of Forecasting
Print ISSN 0277-6693
Electronic ISSN 1099-131X
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 24
Issue 5
Pages 353-368
DOI https://doi.org/10.1002/for.943
Keywords Feedforward neural networks.
Publisher URL http://www3.interscience.wiley.com/cgi-bin/abstract/110574904/ABSTRACT