山东科学2024，Vol.37Issue(4)：56-64,9.DOI:10.3976/j.issn.1002-4026.20230149
基于优化神经网络的沥青混合料力学特性预估
Prediction of mechanical properties of asphalt mixtures based on optimized neural networks
摘要
Abstract
The existing fatigue life prediction of asphalt mixtures is mostly based on traditional fatigue equation fitting;however,due to the multidirectionality of pavement structure and the complexity of materials,the prediction accuracy is often not satisfactory.Therefore,this article establishes an optimized neural network-based model for predicting the strength and fatigue life of asphalt mixtures using indoor indirect tensile tests and verifies the accuracy of the prediction model.The experimental results show that the accuracy of Genetic Algorithm-Back Propagation neural network to predict the fatigue mechanical properties for asphalt mixture is within 4%,which is far superior to traditional fatigue prediction equations and can be used as an effective method to obtain data on the fatigue characteristics of asphalt mixtures.关键词
交通工程/沥青混合料/深度学习模型/强度预测/疲劳寿命预测Key words
traffic engineering/asphalt mixture/deep-learning model/strength prediction/fatigue life prediction分类
交通运输引用本文复制引用
王晓阳,万晨光,王笑风..基于优化神经网络的沥青混合料力学特性预估[J].山东科学,2024,37(4):56-64,9.基金项目
河南省交通运输厅科技项目(2020J-2-5) （2020J-2-5）
