Forecasting sales based on card transactions data
published: Oct. 21, 2015, recorded: October 2015, views: 1420
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Smart cities are an important topic in today’s research problems, with high impact in many domains from economy to transportation, health and living style. The problem addressed in this paper is that of sales forecasting for a specific category of products. We present the results of three regression algorithms, applies on real live data, for predicting the cumulative hourly sales of petrol. The prediction is made for three short term intervals, of 1, 4, and 8 hours into the future. A study has also been conducted in order to identify the amount of historical data required for optimal results.
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