Abstract
We are studying forecasting the number of customers visiting restaurants methods that make integrated use of internal data such as purchase data accumulated by POS systems, external environmental data such as weather and day of the week, and external data such as events. Since the beginning of 2020, the number of customers visiting restaurants has decreased significantly due to COVID-19. It is difficult to forecast the number of customers visiting the restaurant that has changed rapidly due to a sudden event using conventional methods. In this paper, we propose a forecasting method for the number of customers visiting under the conditions of COVID-19 and discuss the results of the analysis, aiming to establish a forecasting method that can cope with changes caused by sudden events.
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