Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …

Metaheuristic algorithms have been widely concerned by scholars because of their global
optimization ability that does not depend on gradient information. In this study, Water Cycle …

When dealing with optimization problems, the introduction of uncertainty will greatly
increase the difficulty of solving the problem. The traditional reliability-based design …

Subset simulation (SS) was known for its computational efficiency in estimating small failure
probabilities as well as reducing emulation demands. The main idea behind SS lies in …

The reliability analysis of complex structures usually involves implicit performance function
and expensive-to-evaluate computational models, which pose a great challenge for the …

To reduce the computational burden for structural reliability analysis involving complex
numerical models, many adaptive algorithms based on surrogate models have been …

In this paper, Bayesian support vector regression (SVR) model is developed for structural
reliability analysis adaptively. Two SVR models, namely, least-square SVR and ε-SVR, are …

With the development of the surrogate-assisted Reliability-Based Design Optimization
(RBDO) methods in recent decade, efficiency has been continuously improved by various …

Time-dependent reliability analysis using surrogate model has drawn much attention for
avoiding the high computational burden. But the surrogate training strategies of existing …

The surrogate-model based active learning method has a satisfactory trade-off between
efficiency and accuracy, which has been widely used in reliability analysis. In this paper, an …