A Deep Neural Network Approach to Predict Overlay Thickness of Asphalt Pavements Using Deflection Parameters and Estimated Traffic-Reference-Cited by-同舟云学术

A Deep Neural Network Approach to Predict Overlay Thickness of Asphalt Pavements Using Deflection Parameters and Estimated Traffic

Published:2022-09 Issue:3 Volume:148 Page:
ISSN:2573-5438
Container-title:Journal of Transportation Engineering, Part B: Pavements
language:en
Short-container-title:J. Transp. Eng., Part B: Pavements

Author:

Haridas Aswani K.¹,Peraka Naga Siva Pavani²,Biligiri Krishna Prapoorna³^ORCID

Affiliation:

1. Former Graduate Researcher, Dept. of Civil and Environmental Engineering, Indian Institute of Technology Tirupati, Tirupati, Andhra Pradesh 517506, India.

2. Senior Assistant Professor, Dept. of Civil Engineering, GMR Institute of Technology Rajam, Rajam, Andhra Pradesh 532127, India.

3. Associate Professor and Head, Dept. of Civil and Environmental Engineering, Indian Institute of Technology Tirupati, Tirupati, Andhra Pradesh 517506, India (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JPEODX.0000388

Reference39 articles.

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2. Performance-Based Models for Flexible Pavement Structural Overlay Design

3. Empirical-Markovian model for predicting the overlay design thickness for asphalt concrete pavement

4. Artificial neural network approach for overlay design of flexible pavements;Abo-Hashema M.;Int. Arab J. Inf. Technol.,2009

5. An K. E. S. W. Lee S. K. Ryu and D. Seo. 2018. “Detecting a pothole using deep convolutional neural network models for an adaptive shock observing in a vehicle driving.” In Proc. 2018 IEEE Int. Conf. on Consumer Electronics (ICCE). New York: IEEE.

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