Prediction of the skid-resistance deterioration in asphalt pavement based on peephole–LSTM neural network-Reference-Cited by-同舟云学术

Prediction of the skid-resistance deterioration in asphalt pavement based on peephole–LSTM neural network

Published:2023-01-28 Issue:2 Volume:24 Page:
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Zhan You¹²,Chen Yining³,Lin Xiuquan¹²,Zhang Yurong¹²,Zhang Allen¹²,Ai Changfa¹²

Affiliation:

1. School of Civil Engineering, Southwest Jiaotong University, Chengdu, People’s Republic of China

2. Highway Engineering Key Laboratory of Sichuan Province, Chengdu, People’s Republic of China

3. Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, Netherlands

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Natural Science Foundation of Sichuan Province

Science and Technology Project of Sichuan Transportation Department

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2023.2277815

Reference41 articles.

1. Rolling Resistance Measurement and Model Development

2. Autonomous detection of concrete damage under fire conditions

3. Evaluating skid resistance of different asphalt concrete mixes

4. ASTM 1845. Standard practice for calculating pavement macrotexture mean profile depth . ASTM International Annual Book of ASTM Standards West Conshohocken PA.

5. ASTM 2009. Standard test method for measuring pavement macrotexture properties using the circular track meter. E2157-09 .

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