DocumentCode :
3195322
Title :
Sales forecasting using neural networks
Author :
Thiesing, Frank M. ; Vornberger, Oliver
Author_Institution :
Dept. of Math. & Comput. Sci., Osnabruck Univ., Germany
Volume :
4
fYear :
1997
fDate :
9-12 Jun 1997
Firstpage :
2125
Abstract :
Neural networks trained with the backpropagation algorithm are applied to predict the future values of time series that consist of the weekly demand on items in a supermarket. The influencing indicators of prices, advertising campaigns and holidays are taken into consideration. The design and implementation of a neural network forecasting system is described that has been developed as a prototype for the headquarters of a German supermarket company to support the management in the process of determining the expected sale figures. The performance of the networks is evaluated by comparing them to two prediction techniques used in the supermarket now. The comparison shows that neural nets outperform the conventional techniques with regard to the prediction quality
Keywords :
backpropagation; feedforward neural nets; sales management; time series; German supermarket; backpropagation; feedforward neural nets; management; sales forecasting; time series; Advertising; Delta modulation; Demand forecasting; Economic forecasting; Exchange rates; Marketing and sales; Mathematics; Multidimensional systems; Neural networks; Weather forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
Type :
conf
DOI :
10.1109/ICNN.1997.614234
Filename :
614234
Link To Document :
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