Support vector machine (SVM) is a powerful machine learning technique relying on the
structural risk minimization principle. The applications of SVM in structural reliability analysis …

The present work reviews the implementation of adaptive metamodeling for reliability
analysis with emphasis in four main types of metamodels: response surfaces, polynomial …

To evaluate failure probability of structures in the most general case is computationally
demanding. The cost can be reduced by using the Response Surface Methodology, which …

This paper deals with the issue on metamodelling (aka surrogate modelling) of nonlinear
stochastic dynamical systems, which are often with multiple input uncertainties Θ∈ R n, viz …

This paper presents a novel procedure based on first-order reliability method (FORM) for
structural reliability analysis in the presence of random parameters and interval uncertain …

The reliability-based design optimization (RBDO) problem involving discrete design
variables and multi-working constraints is tackled with the consideration of the uncertainty …

Long-term service status of a large-scale arch dam is affected by variations of loads and
material properties with randomness and fuzziness. This study aims to resolve the problems …

Aiming at the characteristics of high computational cost, implicit expression and high
nonlinearity of performance functions corresponding to large and complex structures, this …

This paper presents a novel 'hp adaptive'generalized analysis of variance decomposition (G-
ANOVA) for high dimensional stochastic computations. Firstly, an iterative scheme based on …

Three methods of stochastic equivalent linearizations defined in the broad framework of
structural reliability analysis are presented. These methods are (1) the Gaussian equivalent …