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利用BP神经网络反算沥青路面结构层弹性模量的研究
引用本文:杨国良,吴旷怀.利用BP神经网络反算沥青路面结构层弹性模量的研究[J].中山大学学报(自然科学版),2008,47(5).
作者姓名:杨国良  吴旷怀
作者单位:广州大学土木工程学院,广东,广州,510006
摘    要: 基于层状弹性理论,利用BP神经网络预测沥青路面结构层弹性模量。根据常用的路面结构形式,基于层状弹性理论构建路表弯沉值与结构层参数之间的数据库,并以此数据库建立沥青路面结构层弹性模量BP神经网络预测模型。对理论及实测弯沉盆进行结构层弹性模量预测效果检验,并对比分析计算弯沉盆与实测弯沉盆拟合程度。分析表明,建立的沥青路面结构层弹性模量BP神经网络模型具有较好的预测精度,为准确、快速地评价沥青路面结构层的使用状况提供了参考。

关 键 词:沥青路面  结构层弹性模量  预测  BP神经网络  层状弹性理论
收稿时间:2008-05-01;

Backcalculation of Layered Elastic Moduli Of Asphalt Pavement Using BP Neural Network
YANG Guo-liang,WU Kuang-huai.Backcalculation of Layered Elastic Moduli Of Asphalt Pavement Using BP Neural Network[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2008,47(5).
Authors:YANG Guo-liang  WU Kuang-huai
Institution:(School of Civil Engineering, Guangzhou University, Guangzhou 510006,China)
Abstract:Based on layered elastic theory, the layered elastic moduli of asphalt pavement were predicted using BP neural network. According to the types of pavement structure in common use, the database of surface deflections with their corresponding structural parameters was established. BP neural network was developed using the established database and was used to predict the layered elastic moduli of asphalt pavement. The predictive effect of structural elastic moduli backcalculated by theoretical and measured deflection basins was tested. The fitting degree of calculated and measured deflection basins was compared. The analysis results indicated that the developed BP neural network used to predict layered elastic moduli of asphalt pavement was of good predictive accuracy. It would provide the references with the model of BP neural network to accurately and quickly estimate the layer conditions of asphalt pavement.
Keywords:asphalt pavement  layered elastic moduli  prediction  BP neural network  layered elastic theory
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