Machine Learning-Based Seismic Reliability Assessment of Bridge Networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chen, Mengdie | - |
dc.contributor.author | Mangalathu, Sujith | - |
dc.contributor.author | Jeon, Jong-Su | - |
dc.date.accessioned | 2022-07-19T04:50:17Z | - |
dc.date.available | 2022-07-19T04:50:17Z | - |
dc.date.created | 2022-06-03 | - |
dc.date.issued | 2022-07 | - |
dc.identifier.issn | 0733-9445 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/170044 | - |
dc.description.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. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ASCE-AMER SOC CIVIL ENGINEERS | - |
dc.title | Machine Learning-Based Seismic Reliability Assessment of Bridge Networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeon, Jong-Su | - |
dc.identifier.doi | 10.1061/(ASCE)ST.1943-541X.0003376 | - |
dc.identifier.scopusid | 2-s2.0-85128904679 | - |
dc.identifier.wosid | 000796078100005 | - |
dc.identifier.bibliographicCitation | JOURNAL OF STRUCTURAL ENGINEERING, v.148, no.7, pp.1 - 4 | - |
dc.relation.isPartOf | JOURNAL OF STRUCTURAL ENGINEERING | - |
dc.citation.title | JOURNAL OF STRUCTURAL ENGINEERING | - |
dc.citation.volume | 148 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 4 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Construction & Building Technology | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Construction & Building Technology | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.subject.keywordPlus | Machine learning | - |
dc.subject.keywordPlus | Reliability analysis | - |
dc.subject.keywordPlus | Seismology | - |
dc.subject.keywordPlus | Bridge network analyse | - |
dc.subject.keywordPlus | Bridge networks | - |
dc.subject.keywordPlus | Bridge ranking | - |
dc.subject.keywordPlus | Feature importance | - |
dc.subject.keywordPlus | Machine learning models | - |
dc.subject.keywordPlus | Machine-learning | - |
dc.subject.keywordPlus | Network fragilities | - |
dc.subject.keywordPlus | Reliability assessments | - |
dc.subject.keywordPlus | Seismic reliability | - |
dc.subject.keywordPlus | Transportation network | - |
dc.subject.keywordPlus | Risk management | - |
dc.subject.keywordAuthor | Machine learning models | - |
dc.subject.keywordAuthor | Bridge network analysis | - |
dc.subject.keywordAuthor | Network fragility | - |
dc.subject.keywordAuthor | Bridge ranking | - |
dc.subject.keywordAuthor | Feature importance | - |
dc.identifier.url | https://ascelibrary.org/doi/10.1061/%28ASCE%29ST.1943-541X.0003376 | - |
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