Machine learning aided stochastic reliability analysis of spatially variable slopes
This paper presents machine learning aided stochastic reliability analysis of spatially
variable slopes, which significantly reduces the computational efforts and gives a complete …
variable slopes, which significantly reduces the computational efforts and gives a complete …
Efficient reliability analysis considering uncertainty in random field parameters: Trained neural networks as surrogate models
This paper presents an efficient reliability analysis framework, by using trained artificial
neural networks (ANNs) as surrogate models, for geotechnical problems where the random …
neural networks (ANNs) as surrogate models, for geotechnical problems where the random …
A novel uncertainty quantification method for determining deformations and reliabilities of stochastic laminated composite plates with geometric nonlinearity
H Huo, T Yu, J Zhao, G Chen, D Yang - Computer Methods in Applied …, 2024 - Elsevier
Stochastic finite element method (SFEM) for uncertainty quantification is widely applied for
analysis of structures with intrinsic randomness. For determining the geometrically nonlinear …
analysis of structures with intrinsic randomness. For determining the geometrically nonlinear …
[HTML][HTML] Reliability analysis of slope stability by neural network, principal component analysis, and transfer learning techniques
S Zhang, L Ding, M Xie, X He, R Yang… - Journal of Rock Mechanics …, 2024 - Elsevier
The prediction of slope stability is considered as one of the critical concerns in geotechnical
engineering. Conventional stochastic analysis with spatially variable slopes is time …
engineering. Conventional stochastic analysis with spatially variable slopes is time …
[HTML][HTML] Control variates with splitting for aggregating results of Monte Carlo simulation and perturbation analysis
CH Acevedo, MA Valdebenito, IV González, HA Jensen… - Structural Safety, 2024 - Elsevier
Estimation of second-order statistics allows characterizing the uncertainty associated with
the response of stochastic finite element models. Two common approaches for estimating …
the response of stochastic finite element models. Two common approaches for estimating …
Efficient estimation of cumulative distribution functions of multiple failure modes using advanced generalized subset simulation
It is important to estimate the cumulative distribution function (CDF) of a failure mode in a
geotechnical system, because failure of the mode is often characterized by some empirical …
geotechnical system, because failure of the mode is often characterized by some empirical …
[图书][B] Stability of slopes and runout of landslides: stochastic analyses with machine learning
H Xu - 2023 - search.proquest.com
Landslides are natural disasters that often result in severe property damage and facilities.
The main objective of the thesis is to study two critical issues in landslides hazard …
The main objective of the thesis is to study two critical issues in landslides hazard …