Express Delivery Quantity Prediction Based On The Grey GM(1,1) Model

Abstract

To accurately forecast express delivery demand within a specific region and enhance the efficiency of its logistics management system, this study utilizes express delivery volume data from 2018 to 2024 to construct a grey GM(1,1) prediction model. The ratio-of-adjacency test and smoothness ratio test are first applied to verify that the original dataset meets the requirements for grey modeling. Subsequently, the model undergoes a validity test, accuracy test, posterior variance ratio test, and small error probability test, confirming that its fitting performance reaches the first-level accuracy standard. Based on the established model, the express delivery volume from 2025 to 2029 is predicted. The results indicate a sustained upward trend, with the volume estimated to reach 1.5358 million pieces in 2025 and further increase to 4.03 million pieces by 2029. These findings provide a scientific foundation for the rational allocation of regional logistics resources, the optimization of express delivery station layout, and the development of service strategies for express delivery enterprises.