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Modeling of Sales Forecasting in Retail Using Soft Computing Techniques

Authors:
Luis Lobo-da-Costa
Susana Vieira
João Sousa

Keywords: Sales forecasting, Modeling, Soft computing techniques, Retail.

Abstract:
This paper addresses the problem of aggregate daily sales forecasting in retail. Soft computing modeling techniques were applied to this problem. A methodology on how to select the three forecasting periods is presented. The different forecasting horizons consist of a stationary period, a stationary period with disturbances, and a non-stationary period. It is also presented a methodology on how to construct the models' features. These are the weekly and monthly seasonality, the macroeconomic environment translated into the purchasing power, the major promotions and holidays. Further, each model's parameter is developed. The models that presented accurate training performances are finally tested over the forecasting periods, allowing the obtention of reasonably accurate forecasts for the three periods.

Pages: 129 to 134

Copyright: Copyright (c) IARIA, 2013

Publication date: April 21, 2013

Published in: conference

ISSN: 2308-4065

ISBN: 978-1-61208-269-1

Location: Venice, Italy

Dates: from April 21, 2013 to April 26, 2013