Journal of the Korean Asphalt Institute ISSN:2234-0785(Print) 2635-9553(Online) 한국아스팔트학회지

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El Bilali, A., Abdeslam, T., Ayoub, N., Lamane, H., Ezzaouini, M.A. and Elbeltagi, A. (2023). "An interpretable machine learning approach based on DNN, SVR, Extra Tree, and XGBoost models for predicting daily pan evaporation", Journal of Environmental Management, 327, p. 116890.

Hsiao, C.H., Kumar, K. and Rathje, E.M. (2024). "Explainable AI models for predicting liquefaction-induced lateral spreading", Frontiers in Built Environment, 10, p. 1387953.

Kim, T.H., Park, D.S., Woo, D.K., Yoon, C., Lee, J.M. and Son, S.W. (2023). "Influence of Ground Subsidence Size on Settlement Behavior of Buried Pipe-Soil", 2023 Proceeding KSCE 2023 CONVENTION, Yeosu, pp. 730-731. (In Korean)

Lee, S., Kang, J. and Kim, J. (2023). "A Study on Factors Influencing Ground Subsidence and a Risk Analysis Method Using the Attributes of Sewer Pipes", Applied Sciences, 13(17), p. 9714.

Liu, H., Shi, Z., Li, J., Liu, C., Meng, X., Du, Y. and Chen, J. (2021). "Detection of road cavities in urban cities by 3D ground-penetrating radar", Geophysics, 86(3), pp. 25-33.

Liu, L.B., Qian, R.Y., Li, J., Sun, M.G. and Ge, S.C. (2016). "GPR detection of subsurface voids and its validation based on similarity principle", 16th International Conference on Ground Penetrating Radar (GPR), Hong Kong, China, IEEE, pp. 1-4.

Lundberg, S. and Lee, S.-I. (2017). "A unified approach to interpreting model predictions", Neural Information Processing Systems, 30, pp. 4768-4777.

Niazkar, M., Menapace, A., Brentan, B., Piraei, R., Jimenez, D., Dhawan, P. and Righetti, M. (2024). "Applications of XGBoost in water resources engineering: A systematic literature review (Dec 2018-May 2023)", Environmental Modelling & Software, 174, p. 105971.

Park, Y., Kim, D.Y., Kim J.H. and Son, S.W. (2023). "Characteristic of Settlement Behavior of Buried Pipe according to Upper Load in Ground Subsidence", 2023 Proceeding KSCE 2023 CONVENTION, Yeosu, pp. 718-719. (In Korean)

Pereira, M., Burns, D., Orfeo, D., Zhang, Y., Jiao, L., Huston, D. and Xia, T. (2020). "3-D Multistatic Ground Penetrating Radar Imaging for Augmented Reality Visualization", IEEE Transactions on Geoscience and Remote Sensing, 58(8), pp. 5666-5675.

Seo, H.D., Seong, J.Y., Han, T.G. and Son, S.W. (2023). "Analysis of Settlement Behavior according to Size of Buried Pipe in Ground Collapse", 2023 Proceeding KSCE 2023 CONVENTION, Yeosu, pp. 732-733. (In Korean)

Thitimakorn, T., Kampananon, N., Jongjaiwanichkit, N. and Kupongsak, S. (2016). "Subsurface void detection under the road surface using ground penetrating radar (GPR), a case study in the Bangkok metropolitan area", Thailand, Geo-Engineering, 7(2).

Trizoglou, P., Liu, X. and Lin, Z. (2021). "Fault detection by an ensemble framework of Extreme Gradient Boosting (XGBoost) in the operation of offshore wind turbines", Renewable Energy, 179, pp. 945-962.