现代信息科技2025，Vol.9Issue(5)：139-143,5.DOI:10.19850/j.cnki.2096-4706.2025.05.026
基于ARMA与回归修正组合方法的城市轨道交通客流预测研究
Research on Passenger Flow Prediction of Urban Rail Transit Based on Combination Method of ARMA and Regression Correction
廖桂妤1
作者信息
- 1. 宝信软件(广西)有限公司,广西 南宁 530025
- 折叠
摘要
Abstract
Firstly,the paper analyzes the patterns and trends of urban rail transit passenger volume,and selects the Auto-Regression Moving Average(ARMA)model to predict passenger volume.Secondly,to address the issue of reduced accuracy in predicting passenger volume for the next three days or more using the ARMA model,a rolling prediction approach is adopted for optimization.Finally,aiming at the issue of insufficient predictive performance of ARMA rolling prediction for turning points in passenger volume changes,relevant factors affecting changes in passenger volume are analyzed and regression analysis methods are adopted for correction.The results show that the combination method of ARMA rolling prediction and regression correction,compared with the pure ARMA method,not only retains the optimization of passenger volume prediction performance for the next three days or more,but also captures the impact of external factors on passenger volume changes.And it improves the accuracy of passenger flow prediction.关键词
客流预测/城市轨道交通/时间序列/回归分析Key words
passenger flow prediction/urban rail transit/time series/regression analysis分类
交通工程引用本文复制引用
廖桂妤..基于ARMA与回归修正组合方法的城市轨道交通客流预测研究[J].现代信息科技,2025,9(5):139-143,5.
