Prediction of geogrid-reinforced flexible pavement performance using artificial neural network approach-Reference-Cited by-同舟云学术

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Prediction of geogrid-reinforced flexible pavement performance using artificial neural network approach

Published:2017-03-17 Issue:5 Volume:19 Page:1147-1163
ISSN:1468-0629
Container-title:Road Materials and Pavement Design
language:en
Short-container-title:Road Materials and Pavement Design

Author:

Gu Fan¹,Luo Xue²,Zhang Yuqing³^ORCID,Chen Yu²,Luo Rong²,Lytton Robert L.⁴

Affiliation:

1. National Center for Asphalt Technology, 277 Technology Parkway, Auburn, AL 36830, USA

2. Texas A&M Transportation Institute, 3135 TAMU, CE/TTI Bldg. 508B, College Station, TX 77843, USA

3. School of Engineering and Applied Science, Aston University, MB153A, Aston Triangle, Birmingham B4 7ET, UK

4. Zachry Department of Civil Engineering, Texas A&M University, 3136 TAMU, CE/TTI Bldg. 503A, College Station, TX 77843, USA

Funder

National Cooperative Highway Research Program

Publisher

Informa UK Limited

Subject

Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/14680629.2017.1302357

Reference33 articles.

1. Effect of Reinforcement on Resilient and Permanent Deformations of Base Course Material

2. Natural Gradient Works Efficiently in Learning

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