Next: Introduction
Short Term Prediction of Sales in Supermarkets
Frank M. Thiesing, Ulrich Middelberg, Oliver Vornberger
Department of Mathematics/Computer Science
University of Osnabrück
D-49069 Osnabrück, Germany
Frank.Thiesing@GAD.de
Abstract:
In this paper artificial neural networks are applied to a short term forecast of the sale of articles
in supermarkets.
The times series of sales, prices and advertising campaigns are modelled to fit into feedforward multilayer perceptron networks
that are trained by the back-propagation algorithm.
Several net topologies and training parameters have been compaired.
For enhancement the back-propagation algorithm has been parallelized in different manners.
One batch and two on-line training algorithms are implemented
on parallel systems with both the runtime environments PARIX and PVM.
The research will lead to a practical forecasting system for supermarkets.
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