Research on Logistics Cargo Volume Forecasting Based on SETAR Model

Abstract

With the rapid development of e-commerce platforms, logistics networks have ushered in new challenges. In order to predict the cargo volume of logistics routes over a period of time, this paper takes a transportation network as an example, and calibrates three routes as observation points based on the cargo volume of historical logistics routes. Selects a SETAR model with more time considerations than time series, establishes an AR model in each subinterval by setting the upper limit of the number of model orders, delay steps and the number of thresholds, and then changes the threshold value to select the optimal threshold value is selected by the AIC criterion. Then the number of delay steps is changed and the procedure is repeated to achieve the optimal prediction result. Finally, the prediction results of cargo transportation volume of the three routes are obtained. This study is important for the rational arrangement of logistics transportation resources.