首页 | 本学科首页   官方微博 | 高级检索  
     检索      

时间序列在路面平整度预测中的应用
引用本文:倪富健,方昱,薛智敏.时间序列在路面平整度预测中的应用[J].东南大学学报(自然科学版),2006,36(4):634-637.
作者姓名:倪富健  方昱  薛智敏
作者单位:东南大学交通学院,南京,210096;安徽省高速公路总公司,合肥,230001;福建省高速公路养护工程有限公司,福州,350001
摘    要:为了解决国际平整度指数IRI预测模型准确性不高的问题,以京沪高速公路实测IRI数据为基础,对log istic回归、多元回归、时间序列这3种建模方法分别进行分析.并根据京沪高速公路平整度实测数据,建立了几个有不同数量滞后值的时间序列路面平整度预测模型,根据与实测值的比较,找出最优的时间序列路面平整度预测模型.分析结果表明:利用传统的log istic回归和多元回归方法难以建立准确预测路面平整度发展趋势的模型;时间序列方法具有较高的预测精度,且其易修正性是其他预测方法所不具备的.

关 键 词:时间序列  logistic回归  多元回归  IRI
文章编号:1001-0505(2006)04-0634-04
收稿时间:11 29 2005 12:00AM
修稿时间:2005-11-29

Prediction of pavement roughness with time series autoregression model
Ni Fujian,Fang Yu,Xue Zhimin.Prediction of pavement roughness with time series autoregression model[J].Journal of Southeast University(Natural Science Edition),2006,36(4):634-637.
Authors:Ni Fujian  Fang Yu  Xue Zhimin
Institution:1. College of Transportation, Southeast University, Nanjing 210096, China;2. Anhui Province Highway Corporation, Hefei 230001, China;3.Fujian Province Highway Corporation, Fuzhou 350001, China
Abstract:Prediction model of international roughness index(IRI) has a disadvantage of poor precision.Based on the IRI data of Jinghu freeway,three kinds of IRI prediction methods are analyzed in the paper: logistic regression method,multi-regression method,and time series method.With the IRI of Jinghu freeway,a time series prediction model of IRI with different number lag values is established, and by the comparison with actual IRI value,the best prediction model, time series prediction model of IRI is found.The result shows that: logistic regression model and multi-regression model can not work well to predict the trend of IRI;time series model of IRI can predict the trend of IRI very well,and its easiness of correction is unique.
Keywords:time series  logistic model  regression model  IRI
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号