Large-Scale Visual Data–Driven Probabilistic Risk Assessment of Utility Poles Regarding the Vulnerability of Power Distribution Infrastructure Systems-Reference-Cited by-同舟云学术

Large-Scale Visual Data–Driven Probabilistic Risk Assessment of Utility Poles Regarding the Vulnerability of Power Distribution Infrastructure Systems

Published:2021-10 Issue:10 Volume:147 Page:04021121
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Kim Jaeyoon¹^ORCID,Kamari Mirsalar²,Lee Seulbi³,Ham Youngjib⁴^ORCID

Affiliation:

1. Ph.D. Student, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843. ORCID: .

2. Ph.D. Student, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843.

3. Postdoctoral Research Associate, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843.

4. Assistant Professor, Dept. of Construction Science, Texas A&M Univ., 3137 TAMU, College Station, TX 77843 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0002153

Reference60 articles.

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2. AEP (American Electric Power) Texas. 2017. “AEP Texas Hurricane Harvey restoration.” Accessed December 31 2019. https://www.aeptexas.com/info/news/viewRelease.aspx?releaseID=2339.

3. Framework for Measuring the Resilience of Utility Poles of an Electric Power Distribution Network

4. Automatic Assessment and Prediction of the Resilience of Utility Poles Using Unmanned Aerial Vehicles and Computer Vision Techniques

5. High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data

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