Characterizing the Performance of Interstate Flexible Pavements Using Artificial Neural Networks and Random Parameters Regression-Reference-Cited by-同舟云学术

Characterizing the Performance of Interstate Flexible Pavements Using Artificial Neural Networks and Random Parameters Regression

Published:2020-06 Issue:2 Volume:26 Page:04020010
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Yamany Mohamed S.¹^ORCID,Saeed Tariq Usman²^ORCID,Volovski Matthew³^ORCID,Ahmed Anwaar⁴^ORCID

Affiliation:

1. Doctoral Candidate, Lyles School of Civil Engineering, Purdue Univ., West Lafayette, IN 47907 (corresponding author). ORCID: .

2. Research Affiliate, Center for Connected and Automated Transportation, Lyles School of Civil Engineering, Purdue Univ., West Lafayette, IN 47907. ORCID: .

3. Assistant Professor, Dept. of Civil and Environmental Engineering, Manhattan College, 4513 Manhattan College Pkwy., Riverdale, NY 10471. ORCID: .

4. Associate Professor, National Univ. of Science and Technology, Risalpur, NUST Main Campus, H-12, Islamabad, Pakistan. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IS.1943-555X.0000542

Reference68 articles.

1. Deterministic Performance Prediction Model for Rehabilitation and Management of Flexible Pavement

2. Back-calculation of transition probabilities for Markovian-based pavement performance prediction models

3. International Roughness Index prediction model for flexible pavements

4. ESTIMATION OF REST PERIODS FOR NEWLY CONSTRUCTED/RECONSTRUCTED PAVEMENTS

5. Pavement Repair Marginal Costs: Accounting for Heterogeneity Using Random-Parameters Regression

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