摘要
基于层状弹性体系理论,建立BP人工神经网络反演沥青路面沥青面层弹性模量预测模型,利用BP人工神经网络预测沥青路面沥青面层弹性模量。理论弯沉盆和实测弯沉盆反演沥青面层弹性模量的结果表明,建立的BP人工神经网络反演沥青路面沥青面层弹性模量模型具有良好的预测精度和可靠性,为评价沥青路面的沥青面层性能状况提供了参考。
Based on layered elastic theory,the elastic modulus of asphalt course in asphalt pavement was predicted using BP artificial neural network.According to the types of pavement structure in common use,the database of surface deflections with their corresponding structural parameters of asphalt course based on layered elastic theory was established.The elastic modulus backcalculation model of asphalt course in asphalt pavement was developed using BP artificial neural network to predict.The predictive results of asphalt course elastic modulus backcalculation using theoretical deflection basin and measured deflection basin indicate that the elastic modulus backcalculation model of asphalt course in asphalt pavement is of good predictive accuracy and reliability.It would provide the references with the elastic modulus backcalculation model of asphalt course to accurately and quickly estimate the conditions of asphalt course in asphalt pavement.
出处
《科技创新导报》
2015年第29期91-93,95,共4页
Science and Technology Innovation Herald
基金
广东省大学生创新创业训练计划项目(201411078040)
国家大学生创新创业训练计划项目(201511078010)
关键词
BP人工神经网络
路表弯沉盆
弹性模量反演
沥青面层
沥青路面
BP artificial neural network
Ssurface deflection basin of pavement
Elastic modulus backcalculation
Asphalt course
Asphalt pavement