Sales Prediction through Neural Networks for a Small Dataset

Author
Keywords
Abstract
Sales forecasting allows firms to plan their production outputs, which contributes to optimizing firms' inventory management via a cost reduction. However, not all firms have the same capacity to store all the necessary information through time. So, time-series with a short length are common within industries, and problems arise due to small time series does not fully capture sales' behavior. In this paper, we show the applicability of neural networks in a case where a company reports a short time-series given the changes in its warehouse structure. Given the neural networks independence form statistical assumptions, we use a multilayer-perceptron to get the sales forecasting of this enterprise. We find that learning rates variations do not significantly increase the computing time, and the validation fails with an error minor to five percent.
Year of Publication
2019
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
5
Issue
Special Issue on Artificial Intelligence Applications
Number
4
Number of Pages
35-41
Date Published
03/2019
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/journal/sites/default/files/files/2018/04/ijimai_5_4_4_pdf_17317.pdf
DOI
10.9781/ijimai.2018.04.003
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