dc.citation.conferencePlace |
KO |
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dc.citation.conferencePlace |
Seoul National University |
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dc.citation.title |
13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 |
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dc.contributor.author |
Lee, Jaebeom |
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dc.contributor.author |
Lee, Kyoung-Chan |
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dc.contributor.author |
Lee, Young-Joo |
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dc.date.accessioned |
2024-02-01T00:09:53Z |
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dc.date.available |
2024-02-01T00:09:53Z |
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dc.date.created |
2020-01-04 |
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dc.date.issued |
2019-05-27 |
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dc.description.abstract |
Vertical deflection of a high-speed railway bridge is one of the important indicators for managing the safety and running stability of a vehicle. Therefore, efforts have been made to develop sensors for measuring the deflection and predicting its short- and long-term future values. However, the vertical deflection of a railway bridge is stochastic because it involves various sources of uncertainty, which may cause errors in physics-based prediction models. This study proposes a Bayesian approach to build a probabilistic prediction model for the vertical deflection of a railway bridge. For this task, a Gaussian process is introduced to construct a covariance matrix with multiple kernels. Thereafter, actual vision-based measurements, measuring time, and temperature data are used to optimize the hyperparameters of the kernels. As a result, the proposed approach provides a probabilistic prediction interval as well as a predictive mean of the vertical deflections of the bridge. This approach is applied to an actual high-speed railway bridge in the Republic of Korea, and the corresponding analysis results and their performance are discussed. |
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dc.identifier.bibliographicCitation |
13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 |
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dc.identifier.scopusid |
2-s2.0-85070972973 |
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dc.identifier.uri |
https://scholarworks.unist.ac.kr/handle/201301/79728 |
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dc.language |
영어 |
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dc.publisher |
Civil Engineering Risk and Reliability Association (CERRA) |
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dc.title |
Probabilistic prediction of vertical deflection for high-speed railway bridges using a Gaussian process |
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dc.type |
Conference Paper |
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dc.date.conferenceDate |
2019-05-26 |
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