RESEARCH ON THE PREDICTION OF EMERGENCY TRANSPORTATION OF E-COMMERCE LOGISTCIS PARCELS BASED ON ARIMA TIME SERIES
Rong Rong, Shi Hu, Hang Yang, Xu Han · Journal of Computer Science and Electrical Engineering · 2024
The time series prediction model can be used to predict the future change trend of the series to provide support for decision-making. For the prediction study of multivariate time series, in order to solve the prediction model of the cargo volume of the line and predict the daily cargo volume of each line during January 2023, if the new logistics site and transportation route are added, how to add more forecast is reasonable, and further explore the robustness of the established network. Using ARIMA (time series prediction model) and MATLAB programming, and combined with the topsis algorithm of entropy weight method, the prediction model of e-commerce emergency parcel transportation based on ARIMA time series is constructed to solve the problem of emergency logistics package.