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Articles

Variation of CPTu-based transformation models for undrained shear strength of Finnish clays

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Pages 262-270 | Received 09 May 2019, Accepted 13 Jul 2019, Published online: 24 Jul 2019

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Jiabao Xu, Lulu Zhang, Jinhui Li, Zijun Cao, Haoqing Yang & Xiangyu Chen. (2021) Probabilistic estimation of variogram parameters of geotechnical properties with a trend based on Bayesian inference using Markov chain Monte Carlo simulation. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards 15:2, pages 83-97.
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Kok-Kwang Phoon & C. Hsein Juang. (2019) Georisk special issue in Honour and Memory of Professor Tien H. Wu. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards 13:4, pages 237-241.
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M.M. Othman, R. Hen-Jones, C. Zapata, E. Jiménez, F. De Luca, E.A. Holcombe & P.J. Vardanega. (2023) Geotechnical variability of the soils of Quito, Ecuador: a geodatabase study. Bulletin of Engineering Geology and the Environment 82:11.
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Pin ZhangZhen-Yu YinYin-Fu Jin. (2022) Bayesian neural network-based uncertainty modelling: application to soil compressibility and undrained shear strength prediction. Canadian Geotechnical Journal 59:4, pages 546-557.
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Te Xiao, Hai-Feng Zou, Ke-Sheng Yin, Yu Du & Li-Min Zhang. (2021) Machine learning-enhanced soil classification by integrating borehole and CPTU data with noise filtering. Bulletin of Engineering Geology and the Environment 80:12, pages 9157-9171.
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K.S. YinL.M. ZhangH.J. WangH.F. ZouJ.H. Li. (2021) Marine soil behaviour classification using piezocone penetration test (CPTu) and borehole records. Canadian Geotechnical Journal 58:2, pages 190-199.
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Dipanjan Dutta & Sumanta Haldar. 2020. Advances in Offshore Geotechnics. Advances in Offshore Geotechnics 405 415 .

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