Estimation of trend and random components of conditional random field using Gaussian process regression
A method is proposed for simultaneously estimating the trend and random component of soil
properties at arbitrary locations using Gaussian process regression with the superposition of …
properties at arbitrary locations using Gaussian process regression with the superposition of …
Optimization of site investigation program for reliability assessment of undrained slope using Spearman rank correlation coefficient
Site investigation programs (eg, boreholes) are crucial in characterizing soil properties and
stratigraphic configurations. However, the traditional borehole patterns are generally of …
stratigraphic configurations. However, the traditional borehole patterns are generally of …
[HTML][HTML] Joint estimation of PM2. 5 and O3 over China using a knowledge-informed neural network
China has currently entered a critical stage of coordinated control of fine particulate matter
(PM 2.5) and ozone (O 3), it is thus of tremendous value to accurately acquire high …
(PM 2.5) and ozone (O 3), it is thus of tremendous value to accurately acquire high …
Quasi-site-specific multivariate probability distribution model for sparse, incomplete, and three-dimensional spatially varying soil data
In a previous work, the first two authors proposed a data-driven method that can construct a
site-specific multivariate probability density function model for soil properties using sparse …
site-specific multivariate probability density function model for soil properties using sparse …
CPT-based probabilistic liquefaction assessment considering soil spatial variability, interpolation uncertainty and model uncertainty
In engineering practice, simplified procedure based on cone penetration test (CPT) results is
widely used for evaluating soil liquefaction potential. Since the CPT-based simplified …
widely used for evaluating soil liquefaction potential. Since the CPT-based simplified …
Data-driven simulation of two-dimensional cross-correlated random fields from limited measurements using joint sparse representation
Cross-correlated random fields are an essential tool for simultaneously modeling both auto-
and cross-correlation structures of spatial or temporal quantities in stochastic analysis of …
and cross-correlation structures of spatial or temporal quantities in stochastic analysis of …
Fast stratification of geological cross-section from CPT results with missing data using multitask and modified Bayesian compressive sensing
T Zhao, Y Wang, SF Lu, L Xu - Canadian Geotechnical Journal, 2023 - cdnsciencepub.com
Since cone penetration test (CPT) is reasonably rapid, affordable, and repeatable, it has
been widely used in situ for subsurface soil stratification and classification in geological and …
been widely used in situ for subsurface soil stratification and classification in geological and …
[HTML][HTML] An improved BUS approach for Bayesian inverse analysis of soil parameters incorporating extensive field data
This study addresses the complexities encountered when integrating site-specific field data
into the Bayesian inverse analysis of soil parameters in geotechnical structures. Traditional …
into the Bayesian inverse analysis of soil parameters in geotechnical structures. Traditional …
A decomposed Karhunen–Loève expansion scheme for the discretization of multidimensional random fields in geotechnical variability analysis
B Zhu, T Hiraishi - Stochastic Environmental Research and Risk …, 2024 - Springer
The efficient discretization of a multidimensional random field with high definition and large
geometric size remains a significant challenge. Compared with the simulation of one …
geometric size remains a significant challenge. Compared with the simulation of one …
Efficient simulation of multivariate three-dimensional cross-correlated random fields conditioning on non-lattice measurement data
It is challenging to simulate large-scale or fine-resolution multivariate three-dimensional
(3D) cross-correlated conditional random fields because of computational issues such as …
(3D) cross-correlated conditional random fields because of computational issues such as …