Work

China‐Europe Railway Express Freight Volume Forecasting With a Novel SARIMAX‐BNN Model

Year: 2025

Type: article

Abstract: ABSTRACT This study proposes a hybrid SARIMAX‐BNN model to forecast China‐Europe Railway Express (CR Express) freight volume, addressing challenges such as nonlinearity, temporal dependence, and high volatility. Spearman rank correlation is used to select key influencing factors to optimise SARIMAX inputs. The SARIMAX model captures trend and residuals, while the BNN learns nonlinear residual patterns. Final predictions are obtained by combining both models. Using annual and monthly freight data from Xi'an CR Express, the proposed model achieves an MAE of 0.16 (10k tonnes) and a MAPE of 0.90% on the annual dataset and an MAE of 14.53 TEU with a MAPE of 0.05% on the monthly dataset, outperforming all baseline methods. This approach improves forecasting accuracy and supports better operational decisions.

Source: IET Intelligent Transport Systems

DOI: 10.1049/itr2.70095

Authors: Rong Zhang, Minshan Zhao

Institution: Beijing Jiaotong University

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,790