Load-Capacity Rating of Bridge Populations through Machine Learning: Application of Decision Trees and Random Forests-Reference-Cited by-同舟云学术

Load-Capacity Rating of Bridge Populations through Machine Learning: Application of Decision Trees and Random Forests

Published:2017-10 Issue:10 Volume:22 Page:04017076
ISSN:1084-0702
Container-title:Journal of Bridge Engineering
language:en
Short-container-title:J. Bridge Eng.

Author:

Alipour Mohamad¹^ORCID,Harris Devin K.²,Barnes Laura E.³,Ozbulut Osman E.⁴,Carroll Julia⁵

Affiliation:

1. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., Charlottesville, VA 22904-4742 (corresponding author). ORCID: .

2. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., Charlottesville, VA 22904-4742.

3. Assistant Professor, Dept. of Systems and Information Engineering, Univ. of Virginia, 151 Engineer’s Way, Charlottesville, VA 22904-4747.

4. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., Charlottesville, VA 22904-4742.

5. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., Charlottesville, VA 22904-4742.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29BE.1943-5592.0001103

Reference48 articles.

1. Alipour M. Gheitasi A. Harris D. K. Ozbulut O. E. and Barnes L. E. (2016). “A data-driven approach for automated operational safety evaluation of the national inventory of reinforced concrete slab bridges.” Transportation Research Board (TRB) 95th Annual Meeting Transportation Research Board Washington DC.

2. Pattern extraction for high-risk accidents in the construction industry: A data-mining approach;Amiri M.;Int. J. Inj. Control Saf. Promotion,2016

3. ASCE. (2013). “Report card for America’s infrastructure.” 〈http://www.infrastructurereportcard.org/〉 (July 25 2015).

Cited by 45 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven shear capacity analysis of headed stud in steel-UHPC composite structures;Engineering Structures;2024-12

2. Machine learning approaches for predicting shielding effectiveness of carbon fiber-reinforced mortars;Case Studies in Construction Materials;2024-07

3. Bridging Convolutional Neural Networks and Transformers for Efficient Crack Detection in Concrete Building Structures;Sensors;2024-06-30

4. Development and Utilization of Bridge Data of the United States for Predicting Deck Condition Rating Using Random Forest, XGBoost, and Artificial Neural Network;Remote Sensing;2024-01-16

5. Machine Learning Techniques for Predicting the Peak Response of Reinforced Concrete Beam Subjected to Impact Loading;2024