基于神经网络-遗传算法的功能性沥青路面材料优选  

Optimization of functional asphalt pavement based on GA-ANN

作　　者：孟繁宇[1] 潘晓东[1] 

机构地区：[1]同济大学交通运输工程学院,上海201804

出　　处：《吉林大学学报（工学版）》2013年第S1期535-538,共4页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家级大学生创新创业计划项目(201210247053)

摘　　要：根据功能性沥青路面中全面性能的要求,采用GA-ANN法对沥青路面中的矿料配比进行优化,综合考察沥青混合料矿料类型、沥青类型和填加剂等因素。以动稳定度作为评价指标,综合考究其残留稳定度、蠕变速率、摩擦因数、渗水系数以及空隙率等因素,从而提出了功能性沥青路面矿料配比的最佳优化方案。综合评价结果显示方案是可行且有效的,在一定程度上能够满足我国公路运输事业对功能性沥青路面材料配比的要求。According to the comprehensive functional asphalt pavement performance requirements,by GA-ANN optimize mineral aggregate ratio of asphalt pavement was optimized using GA-ANN.A seties of factors such as asphalt mixture type of mineral aggregate,asphalt type,and fill plus were comprenensively surveyed.Evaluation indicators integrated dynamic stability as elegant residual stability,creep rate,friction coefficient and permeability coefficient,and porosity and other factors,which put forward the best strategies for optimizing functional asphalt pavement mineral aggregate ratio.Comprehensive evaluation results show that the scheme is feasible and effective,and to some extent,to meet the requirements of the cause of chinese road transport functional asphalt pavement material ratio.

关 键 词：道路工程 沥青路面 优化 神经网络-遗传算法 

分 类 号：U414[交通运输工程—道路与铁道工程]