dc.citation.conferencePlace |
KO |
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dc.citation.conferencePlace |
Jeollanam-do, Korea |
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dc.citation.title |
2019 International Symposium on Sea-Crossing Bridges |
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dc.contributor.author |
Lee, Jaebeom |
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dc.contributor.author |
Lee, Young-Joo |
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dc.date.accessioned |
2024-01-31T23:36:52Z |
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dc.date.available |
2024-01-31T23:36:52Z |
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dc.date.created |
2020-01-04 |
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dc.date.issued |
2019-10-25 |
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dc.description.abstract |
For structural management purposes, various sensing techniques have been applied to monitor the structural deflection of cable-stayed bridges, such as girder deflection and pylon incline. However, it is not an easy task to make effective decisions on bridge management based on measurement data. This study proposes a new Bayesian method for the probabilistic prediction of the deflection of cable-stayed bridges. To build a probabilistic prediction model based on monitoring data, the proposed method introduces the Gaussian process regression with a new combination of kernel functions. The proposed method is applied to an actual cable-stayed bridge in the Republic of Korea, and a probabilistic prediction of the pylon incline is made successfully. |
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dc.identifier.bibliographicCitation |
2019 International Symposium on Sea-Crossing Bridges |
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dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/79011 |
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dc.publisher |
Korean Institute of Bridge and Structural Engineers |
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dc.title |
Bayesian prediction of deflection based on measurement data for cable-stayed bridges |
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dc.type |
Conference Paper |
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dc.date.conferenceDate |
2019-10-24 |
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