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Logistics Demand Forecast of Fresh Food E-Commerce Based on Bi-LSTM Model
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作者 Shifeng Ni Yan Peng Zijian Liu 《Journal of Computer and Communications》 2022年第9期51-65,共15页
Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales ... Fresh products have the characteristics of perishable, small batch and high frequency. Therefore, for fresh food e-commerce enterprises, market demand forecasting is particularly important. This paper takes the sales data of a fresh food e-commerce enterprise as the logistics demand, analyzes the influence of time and meteorological factors on the demand, extracts the characteristic factors with greater influence, and proposes a logistics demand forecast scheme of fresh food e-commerce based on the Bi-LSTM model. The scheme is compared with other schemes based on the BP neural network and LSTM neural network models. The experimental results show that the Bi-LSTM model has good prediction performance on the problem of logistics demand prediction. This facilitates further research on some supply chain issues, such as business decision-making, inventory control, and logistics capacity planning. 展开更多
关键词 Data Analysis Bi-LSTM Fresh Food E-Commerce logistics Demand Forecast
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