Study on Q-value prediction ahead of tunnel excavation face using recurrent neural network |
Hong, Chang-Ho
(Div. of Radioactive Waste Disposal Research, KAERI)
Kim, Jin (Dept. of Civil and Environmental Engineering, KAIST) Ryu, Hee-Hwan (Structural & Seismic Tech. Group, KEPCO Research Institute) Cho, Gye-Chun (Dept. of Civil and Environmental Engineering, KAIST) |
1 | Barton, N., Lien, R., Lunde, J. (1974), "Engineering classification of rock masses for the design of tunnel support", Rock Mechanics, Vol. 6, No. 4, pp. 189-236. DOI |
2 | Bieniawski, Z.T. (1973), "Engineering classification of jointed rock masses", The Civil Engineer in South Africa, Vol. 15, No. 12, pp. 335-343. |
3 | Hochreiter, S., Schmidhuber, J. (1997), "Long short-term memory", Neural Computation, Vol. 9, No. 8, pp. 1735-1780. DOI |
4 | Jung, J.H., Kim, B.K., Chung, H.Y., Kim, H.M., Lee, I.M. (2019), "A ground condition prediction ahead of tunnel face utilizing time series analysis of shield TBM data in soil tunnel", Journal of Korean Tunnelling and Underground Space Association, Vol. 21, No. 2, pp. 227-242. DOI |
5 | Kim, H.M., Lee, I.M., Hong, C.H. (2019a), "Effect of RMR and rock type on tunnel drilling speed", Journal of Korean Tunnelling and Underground Space Association, Vol. 21, No. 4, pp. 561-571. DOI |
6 | Kim, H.Y., Cho, L.H., Kim, K.S. (2019b), "Rock classification prediction in tunnel excavation using CNN", Journal of the Korean Geotechnical Society, Vol. 35, No. 9, pp. 37-45. DOI |
7 | Kim, K.S., Kim, J.H., Jeong, L.C., Lee, I.M., Cho, G.C. (2015), "Development for prediction system of TBM tunnel face ahead using probe drilling equipment and drilled hole imaging equipment", Journal of Korean Tunnelling and Underground Space Association, Vol. 17, No. 3, pp. 393-401. DOI |
8 | Ryu, H.H., Oh, T.M., Cho, G.C., Kim, K.Y., Lee, K.R., Lee, D.S. (2014), "Probabilistic relationship between Q-value and electrical Resistivity", KSCE Journal of Civil Engineering, Vol. 18, No. 3, pp. 780-786. DOI |
9 | Zhang, S., Bamakan, S.M.H., Qu, Q., Li, S. (2018), "Learning for personalized medicine: A comprehensive review from a deep learning perspective", IEEE Reviews in Biomedical Engineering, Vol. 12, pp. 194-208. DOI |
10 | Zhao, H., Chen, Z., Jiang, H., Jing, W., Sun, L., Feng, M. (2019), "Evaluation of three deep learning models for early crop classification using sentinel-1A imagery time series-A case study in Zhanjiang, China", Remote Sensing, Vol. 11, No. 22, pp. 2673. DOI |