J4 ›› 2014, Vol. 27 ›› Issue (3): 66-72.doi: 10.3976/j.issn.1002-4026.2014.03.013

• 交通运输专栏 • 上一篇    下一篇

基于时间序列模型的轨道质量指数预测研究

宋博洋   

  1. 北京交通大学交通运输学院,北京 100044
  • 收稿日期:2014-02-15 出版日期:2014-06-20 发布日期:2014-06-20
  • 作者简介:宋博洋(1990-),男,硕士,研究方向为交通运输工程,运输系统工程。Email:13125720@bjtu.edu.cn

Time sequence model based track quality index prediction

 SONG Bo-Yang   

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
  • Received:2014-02-15 Online:2014-06-20 Published:2014-06-20

摘要:

       轨道质量指数(TQI)是反映区段轨道整体不平顺的一项重要指标,是一个具有随机性特征的时间序列。本文用灰色系统理论分析TQI序列与各单项指标间的关联度并预测某区段下一次检查的数值;运用ARMA模型对200 m单元区段的TQI序列数据进行研究,分析其变化趋势并对未来一段时间的TQI进行预测。算例分析表明,两个模型的预测精度有所提高,相对误差小于5%。

关键词: 时间序列, ARMA模型, 关联度, 修正GM(1, 1), 轨道质量指数

Abstract:

       Track quality index (TQI), a time series with random characteristics, is an important indicator reflecting the total unevenness of a track segment. We analyze the correlation between TQI sequence and every single indicator with grey theory and predict next inspection value of a certain segment. Moreover, we investigate TQI sequence data for 200 m track segment with autoregressive moving average (ARMA) model, analyze their variation tendency and predict TQI value in future time.Analysis show that the accuracy of each model has been improved, and the relative error is less than 5%.

Key words: time sequence, ARMA model, correlation, fitted GM(1,1), TQI

中图分类号: 

  • U216