A Study on the Analysis of Influencing Factors and Forecasting of Railway Freight Volume in the Hainan Free Trade Port Based on CatBoost

Résumé fourni par la source

Based on the statistical data of Hainan Province from 1994 to 2023, this paper systematically analyzes the influencing factors of railway freight volume and constructs multiple models to predict it. Through Pearson correlation analysis, 12 variables highly correlated with railway freight volume were selected, the CatBoost model was used to uncover the non-linear impact of each factor on freight volume, and a comparative evaluation was conducted with Stepwise Regression, Ridge Regression, the GM (1,1) Grey Model, and Random Forest models. The results show that railway freight turnover, number of employees, waterway freight volume, gross regional product, and the added value of the tertiary industry have a significant impact on railway freight volume, and the CatBoost model outperforms other models on evaluation metrics such as mean relative error and absolute error, possessing higher prediction accuracy and robustness. This research helps to deepen the understanding of the influencing mechanism of railway freight demand in the Hainan region and provides a reference for optimizing regional logistics network layout and formulating transportation policies.

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