Research on retail demand forecasting based on deep learning

In the retail sector, accurate and efficient forecasting of sales for a wide range of products is a vital part of business operations, especially for subsequent sales optimization. This makes extremely high demands on forecasting methods or models. To enable more accurate predictions, we propose an AggDeepar model. Real sales data are used to make predictions. Experimentally, the AggDeepar model has greater applicability and higher accuracy in sales volume time series forecasting.