Modeling on Expansion Behavior of Gwangan Bridge using Machine Learning Techniques and Structural Monitoring Data 


Vol. 33,  No. 6, pp. 42-49, Dec.  2018
10.14346/JKOSOS.2018.33.6.42


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  Abstract

In this study, we have developed a prediction model for expansion and contraction behaviors of expansion joint in Gwangan Bridge using machine learning techniques and bridge monitoring data. In the development of the prediction model, two famous machine learning techniques, multiple regression analysis (MRA) and artificial neural network (ANN), were employed. Structural monitoring data obtained from bridge monitoring system of Gwangan Bridge were used to train and validate the developed models. From the results, it was found that the expansion and contraction behaviors predicted by the developed models are matched well with actual expansion and contraction behaviors of Gwangan Bridge. Therefore, it can be concluded that both MRA and ANN models can be used to predict the expansion and contraction behaviors of Gwangan Bridge without actual measurements of those behaviors.

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  Cite this article

[IEEE Style]

박지현, 신성우, 김수용, "Modeling on Expansion Behavior of Gwangan Bridge using Machine Learning Techniques and Structural Monitoring Data," Journal of the Korean Society of Safety, vol. 33, no. 6, pp. 42-49, 2018. DOI: 10.14346/JKOSOS.2018.33.6.42.

[ACM Style]

박지현, 신성우, and 김수용. 2018. Modeling on Expansion Behavior of Gwangan Bridge using Machine Learning Techniques and Structural Monitoring Data. Journal of the Korean Society of Safety, 33, 6, (2018), 42-49. DOI: 10.14346/JKOSOS.2018.33.6.42.

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