A review and assessment of importance sampling methods for reliability analysis
This paper reviews the mathematical foundation of the importance sampling technique and
discusses two general classes of methods to construct the importance sampling density (or …
discusses two general classes of methods to construct the importance sampling density (or …
Sampling methods for solving Bayesian model updating problems: A tutorial
This tutorial paper reviews the use of advanced Monte Carlo sampling methods in the
context of Bayesian model updating for engineering applications. Markov Chain Monte …
context of Bayesian model updating for engineering applications. Markov Chain Monte …
Dense reinforcement learning for safety validation of autonomous vehicles
One critical bottleneck that impedes the development and deployment of autonomous
vehicles is the prohibitively high economic and time costs required to validate their safety in …
vehicles is the prohibitively high economic and time costs required to validate their safety in …
Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment
Driving intelligence tests are critical to the development and deployment of autonomous
vehicles. The prevailing approach tests autonomous vehicles in life-like simulations of the …
vehicles. The prevailing approach tests autonomous vehicles in life-like simulations of the …
EMCS-SVR: hybrid efficient and accurate enhanced simulation approach coupled with adaptive SVR for structural reliability analysis
In structural reliability analysis, robust and efficient sampling methods that address low
failure probabilities are vital challenges. In this paper, a novel dynamical adaptive enhanced …
failure probabilities are vital challenges. In this paper, a novel dynamical adaptive enhanced …
Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation
X Huang, J Chen, H Zhu - Structural Safety, 2016 - Elsevier
With complex performance functions and time-demanding computation of structural
responses, the estimation of small failure probabilities is a challenging problem in …
responses, the estimation of small failure probabilities is a challenging problem in …
[图书][B] Uncertainty quantification
C Soize - 2017 - Springer
This book results from a course developed by the author and reflects both his own and
collaborative research regarding the development and implementation of uncertainty …
collaborative research regarding the development and implementation of uncertainty …
MCMC algorithms for subset simulation
I Papaioannou, W Betz, K Zwirglmaier… - Probabilistic Engineering …, 2015 - Elsevier
Subset Simulation is an adaptive simulation method that efficiently solves structural
reliability problems with many random variables. The method requires sampling from …
reliability problems with many random variables. The method requires sampling from …
Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles
W Yao, X Chen, W Luo, M Van Tooren, J Guo - Progress in Aerospace …, 2011 - Elsevier
This paper presents a comprehensive review of Uncertainty-Based Multidisciplinary Design
Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace …
Optimization (UMDO) theory and the state of the art in UMDO methods for aerospace …
[图书][B] Bayesian methods for structural dynamics and civil engineering
KV Yuen - 2010 - books.google.com
Bayesian methods are a powerful tool in many areas of science and engineering, especially
statistical physics, medical sciences, electrical engineering, and information sciences. They …
statistical physics, medical sciences, electrical engineering, and information sciences. They …