Expert Knowledge–Guided Bayesian Belief Networks for Predicting Bridge Pile Capacity-Reference-Cited by-同舟云学术

Expert Knowledge–Guided Bayesian Belief Networks for Predicting Bridge Pile Capacity

Published:2023-09 Issue:9 Volume:28 Page:
ISSN:1084-0702
Container-title:Journal of Bridge Engineering
language:en
Short-container-title:J. Bridge Eng.

Author:

Assaad Rayan H.¹^ORCID,Hu Xi²,Hussein Mohab³

Affiliation:

1. Assistant Professor of Construction and Civil Infrastructure, Founding Director of the Smart Construction and Intelligent Infrastructure Systems (SCIIS) Lab, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102 (corresponding author). ORCID: .

2. Ph.D. Candidate, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102.

3. Ph.D. Candidate, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ 07102,

Publisher

American Society of Civil Engineers (ASCE)

Subject

Building and Construction,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JBENF2.BEENG-6096

Reference113 articles.

1. AASHTO (American Association of State Highway and Transportation Officials). 2017. LRFD bridge design specifications. Washington, DC: AASHTO.

2. Alaloul, W. S., M. S. Liew, and N. A. W. Zawawi. 2015. “Delphi technique procedures: A new perspective in construction management research.” In Vol. 802 of Applied Mechanics and Materials, 661–667. Stafa-Zurich, Switzerland: Trans Tech Publications Ltd.

3. Prediction of pile bearing capacity using XGBoost algorithm: Modeling and performance evaluation;Amjad M.;Appl. Sci,2022

4. Developing bridge deterioration models using an artificial neural network;Althaqafi E.;Infrastructures,2022

5. Bridge infrastructure asset management system: Comparative computational machine learning approach for evaluating and predicting deck deterioration conditions;Assaad R.;J. Infrastruct. Syst.,2020

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