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[HTML][HTML] Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review
Landslides are one of the geological disasters with wide distribution, high impact and
serious damage around the world. Landslide risk assessment can help us know the risk of …
serious damage around the world. Landslide risk assessment can help us know the risk of …
GFII: A new index to identify geological features during shield tunnelling
Geological features play an essential role in ensuring the safety and enhancing the
construction efficiency of shield tunnelling. However, owing to the concealed nature of the …
construction efficiency of shield tunnelling. However, owing to the concealed nature of the …
Probabilistic analysis and design of stabilizing piles in slope considering stratigraphic uncertainty
The uncertainty involved in the interpreted geological model may be categorized as the
stratigraphic uncertainty and the properties uncertainty. Note that although the influence of …
stratigraphic uncertainty and the properties uncertainty. Note that although the influence of …
Statistical interpretation of soil property profiles from sparse data using Bayesian compressive sampling
In geotechnical engineering, the number of measurement data obtained from in situ or
laboratory tests is usually sparse, especially for projects of small or medium size …
laboratory tests is usually sparse, especially for projects of small or medium size …
Probabilistic slope stability analysis: state-of-the-art review and future prospects
Conventionally adopted deterministic slope stability analyses do not consider the influence
of uncertainties related to geotechnical properties as well as failure mechanism in slope …
of uncertainties related to geotechnical properties as well as failure mechanism in slope …
Data-driven and physics-informed Bayesian learning of spatiotemporally varying consolidation settlement from sparse site investigation and settlement monitoring …
H Tian, Y Wang - Computers and Geotechnics, 2023 - Elsevier
A digital twin of a geotechnical project (eg, a reclamation or ground improvement project) is
a virtual model that aims to continuously learn from actual observations (eg, site …
a virtual model that aims to continuously learn from actual observations (eg, site …
Estimating locations of soil–rock interfaces based on vibration data during shield tunnelling
This paper proposed an approach for estimating the locations of the soil–rock interfaces
(SRI) based on vibration data during shield tunnelling. Vibration data were collected using …
(SRI) based on vibration data during shield tunnelling. Vibration data were collected using …
Stochastic stratigraphic modeling using Bayesian machine learning
Stratigraphic modeling with quantified uncertainty is an open question in engineering
geology. In this study, a novel stratigraphic stochastic simulation approach is developed by …
geology. In this study, a novel stratigraphic stochastic simulation approach is developed by …
Data-driven development of three-dimensional subsurface models from sparse measurements using Bayesian compressive sampling: A benchmarking study
With the rapid development of computing and digital technologies recently, three-
dimensional (3D) subsurface models for accurate site characterization have received …
dimensional (3D) subsurface models for accurate site characterization have received …
Nonparametric and data-driven interpolation of subsurface soil stratigraphy from limited data using multiple point statistics
An essential task in many geotechnical projects is delineation of subsurface soil stratigraphy
from scatter measurements. Geotechnical engineers often use their knowledge on local …
from scatter measurements. Geotechnical engineers often use their knowledge on local …