中国铁道科学2025，Vol.46Issue(3)：216-228,13.DOI:10.3969/j.issn.1001-4632.2025.03.20
基于STL分解与N-BEATS的铁路货运站短期装车量组合预测模型
Combined Prediction Model of Short-Term Car Loading Volume in Railway Freight Station Based on STL Decomposition and N-BEATS
摘要
Abstract
Aiming at the problem that the time series characteristics of short-term car loading volume in railway freight station are difficult to be extracted due to its volatility and randomness,a combined prediction model STL-N-BEATS based on STL decomposition method and N-BEATS neural network model is proposed.Firstly,the original data is decomposed into trend series,periodic series and residual series by STL decomposition method.Then,the N-BEATS model is used to model each volume and reconstruct the prediction results.Finally,based on the 546 days historical car loading data in 4 freight stations of a railway transportation enterprise,the prediction performance of the proposed model is compared with the other 6 models.The results show that under the test set of station A,the predictions of the other 6 models have a certain lag,while the proposed model can better fit the real value curve,and the 3 indexes including the calculated symmetrical average absolute percentage error,average absolute error and root mean square error are the lowest.This is because the trend series and periodic series obtained by the proposed model after decomposing the time series characteristics dominate the prediction results,reducing the uncertainty and volatility of the overall data.When the prediction step is 3 and 7 days,under the prediction scenario of daily car loading capacity of stations B,C and D,and daily car loading capacity of different destinations and different commodity names of station D,the 3 indexes of the proposed model are still the lowest,which signifies its good prediction performance and generalization ability.关键词
铁路货运/短期装车量预测/深度学习/STL分解方法/N-BEATS模型Key words
Railway freight/Short-term car loading volume prediction/Deep learning/STL decomposition method/N-BEATS model分类
交通工程引用本文复制引用
马亮,陈奕霖,郭进,胡宸瀚,金福才..基于STL分解与N-BEATS的铁路货运站短期装车量组合预测模型[J].中国铁道科学,2025,46(3):216-228,13.基金项目
中国国家铁路集团有限公司科技研究开发计划系统性重大项目(P2024X003) （P2024X003）
中国铁道科学研究院集团有限公司科研开发基金资助项目(2022YJ217) （2022YJ217）
