Takayuki Shuku - Publications

2026

Shuku, T., Phoon, K.K. and Kouno, T. (2026). Solving BM/AirportSoilProperties/2/2025 using simple machine learning algorithms, Geodata and AI, 100063, https://doi.org/10.1016/j.geoai.2025.100063. Click

2025

Shuku, T., Phoon, K.K., Yokota, Y. and Date, K. (2025). l1 trend clustering: Trend estimation, clustering, and change detection for spatial-temporal ground displacement data from satellite remote sensing, Geodata and AI, 3, 100020, https://doi.org/10.1016/j.geoai.2025.100020. Click

2024

Phoon, K.K. and Shuku, T. (2024). Future of Machine Learning in Geotechnics (FOMLIG), 5–6 Dec 2023, Okayama, Japan, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 18(1), 288-303, DOI:10.1080/17499518.2024.2316882. Click

Leung, Y.F., Phoon, K.K., Xiao, T., Shuku, T. and Ching, J. (2024). Report for ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment and Management Committee Fourth Machine Learning in Geotechnics Dialogue on “Machine Learning Supremacy Projects”, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 18:1, 304-313, DOI: 10.1080/17499518.2024.2316879. Click

2023

Phoon, K.K., Shuku, T. and Ching, J. (2023). Uncertainty, Modeling, and Decision Making in Geotechnics, CRC Press. Click

Shuku, T. and Phoon, K.K. (2023). Data-driven subsurface modelling using a Markov random field model, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, https://doi.org/10.1080/17499518.2023.2181973. Click

Shuku, T. and Phoon, K.K (2023). Comparison of data-driven site characterization methods through benchmarking: Methodological and application aspects, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(2). Click

Shuku, T., Phoon, K.K., Ishii, M., Kumagai, T., Yokota, Y. and Date, K. (2023). Probabilistic generic transformation model between two rock mass properties: specific fracture energy and P-wave velocity, Canadian Geotechnical Journal, 60(8). Click

2022

Phoon, K.K., Cao, Z. J., Ji, J., Leung Y. F., Najjar, S., Shuku, T., Tang, C., Yin, Z.Y., Yoshida, I. and Ching, J. (2022). Geotechnical uncertainty, modeling, and decision making, Soils and Foundations, 62(5), 101189. Click

Shuku, T. and Yamamoto, S. (2022). A study on optimal design of geotechnical structures using quantum annealing, Journal of JSCE, 78(2), 116-127. (in Japanese with English abstract) Click

Shuku, T., Ropponen, J., Juntunen, J. and Suito, H. (2022). Data‑driven model of the local wind feld over two small lakes in Jyväskylä, Finland, Meteorology and Atmospheric Physics, 134:18, https://doi.org/10.1007/s00703-021-00857-3. Click

Phoon, K.K., Shuku, T., Ching, J. and Yoshida, I. (2022). Benchmark examples for data-driven site characterization, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards , https://doi.org/10.1080/17499518.2022.2025541. Click

2021

T. Shuku and J. Ching: Case Histories on 2D/3D Underground Stratification Using Sparse Machine Learning, Vol. 6, Issue 4, p.35-47. doi: 10.4417/IJGCH-06-04-03. Click

I. Yoshida and T. Shuku: Soil Stratification and Spatial Variability Estimated Using Sparse Modeling and Gaussian Random Field Theory, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., https://doi.org/10.1061/AJRUA6.0001143. Click

K.K. Phoon, J. Ching and T. Shuku: Challenges in data-driven site characterization, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, DOI: 10.1080/17499518.2021.1896005. Click

T. Shuku and K.K. Phoon: Three-dimensional subsurface modeling using Geotechnical Lasso, Computers and Geotechnics, 133 (2021) 1034068. Click

2020

T. Shuku, K.K. Phoon, I. Yoshida: Trend estimation and layer boundary detection in depth-dependent soil data using sparse Bayesian lasso, Computers and Geotechnics, 128 (2020) 103845. Click

Y. Ikumasa and T. Shuku: Bayesian Updating of Model Parameters by Iterative Particle Filter with Importance Sampling, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., 6(2): 04020007, 2020. Click

2019

J. Juntunen, J Ropponen, T. Shuku, K. Krogerus, T. Huttula: The effect of local wind field on water circulation and dispersion of imaginary tracers in two small connected lakes, Journal of Hydrology, 679, 2019. Click

D. Ousaka, N. Sakano, M. Morita, T. Shuku, K. Sanou, S, Kasahara, S. Oozawa: A new approach to prevent critical cardiac accidents in athletes by real-time electrocardiographic tele-monitoring system: Initial trial in full marathon, J. Cardiol. Cases, 20(1), 35-38, 2019. Click

T. Shibata, T. Shuku, A. Murakami, S. Nishimura, K. Fujisawa, N. Haegawa, S. Nonami: Prediction of long-term settlement and evaluation of pore water pressure using particle filter, Soils and Foundations, 59(1), 67-83, 2019. Click

H. Cheng, T. Shuku, K. Thoeni, P. Tempone, S. Luding and V. Magnanimo: An iterative Bayesian filtering framework for fast and automated calibration of DEM models, Computer Methods in Applied Mechanics and Engineering, 350, 268-294, 2019. Click

H. Cheng, T. Shuku, K. Thoeni and H. Yamamoto: Probabilistic calibration of discrete element simulations using the sequential quasi-Monte Carlo filter, Granular Matter, 20: 11, 2018. Click

2018

T. Shuku, N. Sakano, M. Morita and S. Kasahara: Change detection in vital signs associated with impending death for homecare patients using a pressure-sensing mat, European Journal for Biomedical Informatics, 14(1), pp.42-27, 2018. Click