Research on Emergency Mobilization of Logistics Parcels Based on LSTM Modeling
Wanqing Li, Shiqi Liu, Yun Zeng, Shaoqi Chen, Kehua Lu · 2023
At present, the rapid development of national logistics, how to achieve under the conditions of limited cost to reduce the impact of logistics site deactivation on the logistics network, to ensure the normal operation of the logistics network has become a hot topic. This paper predicts the future parcel freight volume based on the historical data of logistics parcels. First, the data are preprocessed and the time series are decomposed based on the additive model. The effects of seasonal components and trend components of the time series are removed by first-order differencing. Here the freight volume is predicted by the LSTM model. Finally, considering the unexpected events, the number of routes with changes in cargo volume due to the shutdown of DC5, the volume of cargo that cannot flow normally, and the network load are analyzed.