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Stochastic simulation of geological cross-sections from boreholes: A random field approach with Markov Chain Monte Carlo method
A reliable geological cross-section is essential to the design and risk assessment of
underground structures. Random fields are commonly employed to model geological …
underground structures. Random fields are commonly employed to model geological …
[HTML][HTML] Regional 3D geological modeling along metro lines based on stacking ensemble model
X Bian, Z Fan, J Liu, X Li, P Zhao - Underground Space, 2024 - Elsevier
This paper presents a regional 3D geological modeling method based on the stacking
ensemble technique to overcome the challenges of sparse borehole data in large-scale …
ensemble technique to overcome the challenges of sparse borehole data in large-scale …
Spatial variability characterization of clayey waste soils and its impact on probabilistic stability assessment of a landfill slope
Rapid urbanization has caused numerous construction solid waste landfills. Few studies
have explored the impact of multi-source waste soils with remarkable spatial variability on …
have explored the impact of multi-source waste soils with remarkable spatial variability on …
An ensemble learning paradigm for subsurface stratigraphy from sparse measurements and augmented training images
The performance of computer vision-based techniques for stratigraphic modeling relies
heavily on qualified training images to capture the complex stratigraphic connectivity. In …
heavily on qualified training images to capture the complex stratigraphic connectivity. In …
Predicting long-term displacements of deep tunnels using an artificial neural network optimized by sand cat swarm optimization with Chebyshev map
Long-term tunnel displacement prediction is of great engineering significance to tunnel
maintenance and hazard warning. To that end, this paper provides a novel combination idea …
maintenance and hazard warning. To that end, this paper provides a novel combination idea …
Advancing geological modelling and geodata management: a web-based system with AI assessment in Singapore
This paper outlines the development and deployment of the Geodata Modelling and
Management System (GEM2S) in Singapore. GEM2S offers a sophisticated web-based …
Management System (GEM2S) in Singapore. GEM2S offers a sophisticated web-based …
Assessing and Improving the Robustness of Bayesian Evidential Learning in One Dimension for Inverting Time-Domain Electromagnetic Data: Introducing a New …
A Ahmed, L Aigner, H Michel, W Deleersnyder… - Water, 2024 - mdpi.com
Understanding the subsurface is of prime importance for many geological and
hydrogeological applications. Geophysical methods offer an economical alternative for …
hydrogeological applications. Geophysical methods offer an economical alternative for …
Data-driven sparse learning of three-dimensional subsurface properties incorporating random field theory
Geotechnical engineers rely on accurate soil property information for engineering analyses.
However, it is challenging for spatial learning of soil attributes because in-situ geotechnical …
However, it is challenging for spatial learning of soil attributes because in-situ geotechnical …
A flexible and efficient model coupling multi-type data for 2D/3D stratigraphic modeling
Stratigraphic modeling plays a critical role in characterizing subsurface conditions, while it
faces significant uncertainty due to geological heterogeneity and sparse borehole data …
faces significant uncertainty due to geological heterogeneity and sparse borehole data …
Integrated geophysical data and Bayesian evidential learning approach for rockhead estimation and uncertainty quantification
Rockhead estimation and uncertainty quantification are essential for underground
constructions such as tunneling. However, deep boreholes that are required for rockhead …
constructions such as tunneling. However, deep boreholes that are required for rockhead …