摘要
文章以合六叶高速公路历年车辙检测数据为分析对象,建立了高速公路沥青路面车辙聚类灰色预测模型。通过聚类分析方法,将车辙发展相似的路段进行归类,从而减少影响因素考虑不全对模型精度的影响;然后针对聚类分析结果,采用灰色模型,建立沥青路面车辙预测模型,从而解决数据量少和不确定性高的问题。研究结果表明:建立的聚类灰色预测模型精度高,能反映沥青路面车辙的发展规律,满足高速公路沥青路面养护工程的需求。
Using the historical data of rutting test on Hefei-Lu＇an-Yeji expressway as the analysis object, the clustering gray forecasting model of expressway asphalt pavement rutting is established. Through the clustering analysis method, the sections of similar rutting development are classified to reduce the effect of partial consideration of the influence factors on the accuracy of the model. Then based on the clustering analysis results, the asphalt pavement rutting forecasting model is established by using the gray model, which solves the problems of less data volume and high uncertainty. The results show that the clustering gray forecasting model has high precision, which can reflect the developing rules of asphalt pavement rutting, and meet the requirements of expressway asphalt pavement maintenance engineering.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2015年第2期219-221,共3页
Journal of Hefei University of Technology：Natural Science
基金
安徽省交通科技进步计划资助项目(2014-15)
关键词
沥青路面
车辙
聚类分析
灰色系统理论
预测模型
asphalt pavement
rutting
clustering analysis
gray system theory
forecasting model
