This paper leverages the robust performance of Bayesian support vector regression to propose a dynamic pruning strategy for the candidate sample pool.

This paper leverages the robust performance of Bayesian support vector regression to propose a dynamic pruning strategy for the candidate sample pool.

Adaptive surrogate-based reliability analysis methods have garnered significant attention due to their potential to enhance computational efficiency in ...

The proposed approaches showcase superior efficiency and accuracy through illustrations using well-known benchmark problems and complex reliability analysis ...

May 2, 2024 · To reduce the computational burden for structural reliability analysis involving complex numerical models, many adaptive algorithms based on ...

Dynamic pruning-based Bayesian support vector regression for reliability analysis. https://doi.org/10.1016/j.ress.2023.109922 ·.

Oct 22, 2024 · This paper aims to develop a strategy for solving RBDO problems by support vector regression (SVR) under the Bayesian inference, referred to as ...

Solving reliability-based design optimization (RBDO) by combining surrogate models is a powerful tool to deal with the output variation induced by uncertainties ...

Downloadable (with restrictions)! In this paper, Bayesian support vector regression (SVR) model is developed for structural reliability analysis adaptively.

Dynamic pruning-based Bayesian support vector regression for reliability analysis ... Reliability analysis of complex structures based on Bayesian inference.