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Probabilistic Prediction of Vertical Deflection for High-speed Railway Bridges Using a Gaussian Process
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jaebeom | - |
dc.contributor.author | Lee, Kyoung-Chan | - |
dc.contributor.author | Lee, Young-Joo | - |
dc.date.accessioned | 2019-05-14T03:10:43Z | - |
dc.date.available | 2019-05-14T03:10:43Z | - |
dc.date.issued | 2019-05-26 | - |
dc.identifier.citation | 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019 | - |
dc.identifier.isbn | 979-11-967125-0-1 | - |
dc.identifier.other | ICASP13-494 | - |
dc.identifier.uri | https://hdl.handle.net/10371/153561 | - |
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. | - |
dc.description.sponsorship | This research was supported by a grant (19SCIP-B138406-04) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA). This research was also supported by a grant from R&D Program of the Korean Railroad Research Institute, Republic of Korea. | - |
dc.language.iso | en | - |
dc.title | Probabilistic Prediction of Vertical Deflection for High-speed Railway Bridges Using a Gaussian Process | - |
dc.type | Conference Paper | - |
dc.contributor.AlternativeAuthor | 이재범 | - |
dc.contributor.AlternativeAuthor | 이경찬 | - |
dc.contributor.AlternativeAuthor | 이용주 | - |
dc.identifier.doi | 10.22725/ICASP13.494 | - |
dc.sortNo | 506 | - |
dc.citation.pages | 2392-2399 | - |
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