Estimation of economic seismic loss of steel moment-frame buildings using a machine learning algorithm
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hwang, Seong-Hoon | - |
dc.contributor.author | Mangalathu, Sujith | - |
dc.contributor.author | Shin, Jinwon | - |
dc.contributor.author | Jeon, Jong-Su | - |
dc.date.accessioned | 2022-07-06T08:44:00Z | - |
dc.date.available | 2022-07-06T08:44:00Z | - |
dc.date.created | 2022-01-26 | - |
dc.date.issued | 2022-03 | - |
dc.identifier.issn | 0141-0296 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/139360 | - |
dc.description.abstract | In this study, the effect of modeling-related uncertainties on the expected annual losses of modern code-compliant steel moment-frame buildings is analyzed. Probabilistic structural models are initially employed to account for all the critical sources of uncertainty. Then, these structural models are used to develop machine-learning-based prediction models to estimate the expected annual losses and the associated economic contributors; the developed machine-learning-based prediction models exhibit an excellent performance in the prediction of the economic seismic losses of steel frame buildings. The effect of structural-modeling-related uncertainties on each loss contributor is also evaluated; the effect of uncertain modeling parameters is observed to be more pronounced on loss contributors such as demolition and structural collapse losses that are controlled primarily by ground motions with a low probability of earthquake occurrence. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCI LTD | - |
dc.title | Estimation of economic seismic loss of steel moment-frame buildings using a machine learning algorithm | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeon, Jong-Su | - |
dc.identifier.doi | 10.1016/j.engstruct.2022.113877 | - |
dc.identifier.scopusid | 2-s2.0-85123017593 | - |
dc.identifier.wosid | 000772610500003 | - |
dc.identifier.bibliographicCitation | ENGINEERING STRUCTURES, v.254, pp.1 - 14 | - |
dc.relation.isPartOf | ENGINEERING STRUCTURES | - |
dc.citation.title | ENGINEERING STRUCTURES | - |
dc.citation.volume | 254 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 14 | - |
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 | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.subject.keywordPlus | NONSTRUCTURAL COMPONENTS | - |
dc.subject.keywordPlus | EARTHQUAKE DAMAGE | - |
dc.subject.keywordPlus | DRIFT DEMANDS | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | RISK | - |
dc.subject.keywordPlus | STRENGTH | - |
dc.subject.keywordPlus | UNCERTAINTY | - |
dc.subject.keywordAuthor | Expected annual losses | - |
dc.subject.keywordAuthor | Machine learning algorithm | - |
dc.subject.keywordAuthor | Structural-modeling-related uncertainty | - |
dc.subject.keywordAuthor | Steel moment-frame buildings | - |
dc.subject.keywordAuthor | Seismic risk | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0141029622000360?via%3Dihub | - |
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