# [1]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.[doi:10.3969/j.issn.1001-0505.2006.04.030] 　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.[doi:10.3969/j.issn.1001-0505.2006.04.030] 点击复制 时间序列在路面平整度预测中的应用() 分享到： var jiathis_config = { data_track_clickback: true };

36

2006年第4期

634-637

2006-07-20

## 文章信息/Info

Title:
Prediction of pavement roughness with time series autoregression model

1 东南大学交通学院, 南京 210096; 2 安徽省高速公路总公司, 合肥 230001; 3 福建省高速公路养护工程有限公司, 福州 350001
Author(s):
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

Keywords:

U418.62
DOI:
10.3969/j.issn.1001-0505.2006.04.030

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.

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