[1]赵静,吴旺杰,王选仓,等.基于等维灰数递补模型的路面性能预测方法[J].深圳大学学报理工版,2019,36(No.6(599-724)):628-634.[doi:10.3724/SP.J.1249.2019.06628]
　ZHAO Jing,WU Wangjie,WANG Xuancang,et al.Prediction method of pavement performance based on same dimension gray recurrence dynamic model[J].Journal of Shenzhen University Science and Engineering,2019,36(No.6(599-724)):628-634.[doi:10.3724/SP.J.1249.2019.06628]
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基于等维灰数递补模型的路面性能预测方法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第36卷
期数:
2019年No.6(599-724)
页码:
628-634
栏目:
土木建筑工程
出版日期:
2019-11-20

文章信息/Info

Title:
Prediction method of pavement performance based on same dimension gray recurrence dynamic model
文章编号:
201906005
作者:
赵静1; 吴旺杰1; 王选仓1; 李善强1; 2; 房娜仁1; 邓瑞祥1
1）长安大学 公路学院，陕西 西安 7100643；2）广东华路交通科技有限公司，广东 广州 510420
Author(s):
ZHAO Jing1;  WU Wangjie1;  WANG Xuancang1;  LI Shanqiang1;  2;  FANG Naren1;  and DENG Ruixiang1
1) School of Highway, Changan University, Xian710064, Shaanxi Province, P.R.China 2) Guangdong Hua Lu Transportation Technology Co.Ltd, Guangzhou 510420, Guangdong Province, P.R.China
关键词:
道路工程; 灰色GM（1;  1）模型; 等维灰数递补模型; 路面使用性能; 性能预测; 精度
Keywords:
road engineering;  grey GM(1;  1) model;  same dimension gray recurrence dynamic model;  pavement usage performance prediction
分类号:
58010；U416.2
DOI:
10.3724/SP.J.1249.2019.06628
文献标志码:
A
摘要:
为了准确掌握沥青路面使用性能指标的变化趋势，在分析传统静态灰色预测模型不足的基础上，提出了能够有效动态使用新数据的等维灰数递补模型，以车辙指数（rutting depth index, RDI）为例建立了模型，基于该模型对路面状况指数（pavement condition index, PCI）、行驶质量指数（riding quality index, RQI）和横向力指数（skidding resistance index, SRI）等指标进行了预测.结果表明：使用等维灰数递补模型对RDI、PCI、RQI和SRI预测在第3步时,最小误差概率均为1，后验方差比分别为0.1117、0.0654、0.2018和0.1130. 证明了随着步数的增加，其预测结果精度越高，误差越小,表明该方法能够准确地预测路面性能.
Abstract:
In order to accurately grasp the change trend of asphalt pavement performance index, Based on the analysis of the shortcomings of the traditional static grey prediction model, putting forward a prediction model of same dimension gray recurrence dynamic model by which the new data can be used effectively and dynamically. Taking the Rutting Depth Index (RDI) as an example, a model of same dimension gray recurrence dynamic model was established, and based on this model, the indexes such as Pavement Condition Index (PCI), Driving Quality Index (RQI) and Transverse Force Index (SRI) are predicted. The results show that the minimum error probability and the posterior prescription difference ratio are: 1, 0.1117; 1, 0.0654; 1, 0.2018;1 and 0.1130 for RDI, PCI, RQI and SRI prediction in the third step using the same dimension gray recurrence dynamic model. It is proved that the prediction result of the model has higher accuracy and less error than that of pavement performance index.

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备注/Memo

备注/Memo:
Received：2018-12-06；Revised：2019-07-17；Accepted：2019-08-01 Foundation：Science and Technology Project of Guangdong Provincial Transportation Department (Science and Technology-2015-02-011) Corresponding author：Professor WANG Xuangcang．E-mail:wxc2005@163.com Citation：ZHAO Jing，WU Wangjie，WANG Xuancang，et al．Prediction method of pavement performance based on same dimension gray recurrence dynamic model［J］. Journal of Shenzhen University Science and Engineering, 2019, 36(6): 628-634.（in Chinese）
更新日期/Last Update: 2019-11-30