Estimation of the rutting performance of Polyethylene Terephthalate modified asphalt mixtures by adaptive neuro-fuzzy methodology

被引：30

作者：

Moghaddam, Taher Baghaee ^{[1
,3
]}

Soltani, Mehrtash ^{[1
]}

Karim, Mohamed Rehan ^{[1
]}

Shamshirband, Shahaboddin ^{[2
]}

Petkovic, Dalibor ^{[4
]}

Baaj, Hassan ^{[3
]}

机构：

[1] Univ Malaya, Fac Engn, Dept Civil Engn, Ctr Transportat Res, Kuala Lumpur 50603, Malaysia

[2] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Comp Syst & Informat Technol, Kuala Lumpur 50603, Malaysia

[3] Univ Waterloo, Fac Engn, Dept Civil & Environm Engn, Ctr Pavement & Transportat Technol, Waterloo, ON N2L 3G1, Canada

[4] Univ Nis, Fac Mech Engn, Nish 18000, Serbia

来源：

CONSTRUCTION AND BUILDING MATERIALS | 2015年 / 96卷

关键词：

Pavement performance; PET modified asphalt mixtures; Environmental conditions; Experimental ANFIS; Estimation; STONE MASTIC ASPHALT; INFERENCE SYSTEM; RESILIENT MODULUS; PREDICTION; CONCRETE; PARAMETERS; BITUMEN;

D O I：

10.1016/j.conbuildmat.2015.08.043

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

In this paper, the accuracy of soft computing techniques was employed for prediction of the rutting performance of Polyethylene Terephthalate (PET) modified asphalt mixture. The process, which simulates the mixture's deformation, was constructed with adaptive neuro-fuzzy inference system (ANFIS). The inputs were PET percentages, stress levels and temperatures. The performance of proposed system was confirmed by simulation results. The ANFIS results and the results achieved by experiments were compared using root-mean-square error (RMSE) and coefficient of determination. The experimental outcomes suggested that ANFIS approach can be used to improve predictive accuracy and capability of generalization. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：550 / 555

页数：6

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