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基于神经网络-遗传算法的功能性沥青路面材料优选
引用本文:孟繁宇,潘晓东. 基于神经网络-遗传算法的功能性沥青路面材料优选[J]. 吉林大学学报(工学版), 2013, 0(Z1): 535-538
作者姓名:孟繁宇  潘晓东
作者单位:同济大学交通运输工程学院
基金项目: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。

关 键 词:道路工程  沥青路面  优化  神经网络-遗传算法

Optimization of functional asphalt pavement based on GA-ANN
MENG Fan-yu,PAN Xiao-dong. Optimization of functional asphalt pavement based on GA-ANN[J]. Journal of Jilin University:Eng and Technol Ed, 2013, 0(Z1): 535-538
Authors:MENG Fan-yu  PAN Xiao-dong
Affiliation:(School of Transportation Engineering Tongji University,Shanghai 201804,China)
Abstract: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.
Keywords:road engineering  asphalt pavement  optimization  GA-ANN
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