Machine Learning-Based Seismic Reliability Assessment of Bridge Networks
- Title
- Machine Learning-Based Seismic Reliability Assessment of Bridge Networks
- Author
- 전종수
- Keywords
- Machine learning models; Bridge network analysis; Network fragility; Bridge ranking; Feature importance
- Issue Date
- 2022-07
- Publisher
- ASCE-AMER SOC CIVIL ENGINEERS
- Citation
- JOURNAL OF STRUCTURAL ENGINEERING, v. 148, NO. 7, article no. 6022002, Page. 1-4
- Abstract
- Transportation networks are critical components of lifeline systems. They can experience disruptions due to seismic hazards that could lead to severe emergency response and recovery problems. Finding an efficient and effective method to evaluate the seismic reliability of bridge networks is crucial for risk managers. This study proposes a method that can compute the seismic reliability of bridge networks using machine learning techniques. The proposed method is computationally less expensive than existing methods and can be implemented easily in emergency risk management systems. Moreover, it includes information on ranking bridges and prioritizing retrofit plans.
- URI
- https://ascelibrary.org/doi/10.1061/%28ASCE%29ST.1943-541X.0003376https://repository.hanyang.ac.kr/handle/20.500.11754/176822
- ISSN
- 0733-9445;1943-541X
- DOI
- 10.1061/(ASCE)ST.1943-541X.0003376
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > CIVIL AND ENVIRONMENTAL ENGINEERING(건설환경공학과) > Articles
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