Prediction of dynamic modulus of asphalt mixture based on gene expression programming algorithm

被引：0

作者：

Yan, Kezhen ^{[1
]}

Liu, Pei ^{[1
]}

Wang, Xiaoliang ^{[1
]}

机构：

[1] College of Civil Engineering, Hunan University, Changsha

来源：

Jianzhu Cailiao Xuebao/Journal of Building Materials | 2015年 / 18卷 / 06期

关键词：

Asphalt mixture; Dynamic modulus; Gene expression programming (GEP) algorithm; Prediction model; Road works;

D O I：

10.3969/j.issn.1007-9629.2015.06.034

中图分类号：

学科分类号：

摘要：

Gene expression programming (GEP) algorithm was used to predict dynamic modulus of asphalt mixture, with eight main factors of dynamic modulus, i.e. air void (Va), effective binder content (wbeff), viscosity of binder (η), loading frequency (f), the mass fraction of aggregate sieve residue on the sieve size of 19 (ρ34), 9.5 (ρ38), 4.75 mm (ρ4) and aggregate passing rate by the 0.075 mm sieve (ρ200), which constitute the main factors to predict dynamic modulus model of asphalt mixture. GEP algorithm can be applied to establish a dynamic modulus prediction model of asphalt mixture by discrete 8 factors. The results show that between the dynamic modulus predicted and measured values a high correlation is obtained and by compared with Witczak 1999 function model, Korean dynamic modulus prediction model and artificial neural network model, GEP algorithm prediction model has some of superiority over the other models. © 2015, Tongji University. All right reserved.

引用

页码：1106 / 1110

页数：4

共 15 条

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