Sequential most probable point update combining Gaussian process and comprehensive learning PSO for structural reliability-based design optimization
This paper proposes an efficient reliability-based design optimization (RBDO) method that
advantageously decouples comprehensive learning particle swarm optimization (CLPSO) …
advantageously decouples comprehensive learning particle swarm optimization (CLPSO) …
Quantile-based sequential optimization and reliability assessment for shape and topology optimization of plane frames using L-moments
Uncertainty is inevitable in the real physical world, and it is necessary to take into account its
effects on the structural design and optimization processes. In this study a reliability-based …
effects on the structural design and optimization processes. In this study a reliability-based …
Bayesian optimization for robust design of steel frames with joint and individual probabilistic constraints
This work proposes a Bayesian optimization (BO) method for solving multi-objective robust
design optimization (RDO) problems of steel frames under aleatory uncertainty in external …
design optimization (RDO) problems of steel frames under aleatory uncertainty in external …
A novel decoupled approach combining invertible cross-entropy method with Gaussian process modeling for reliability-based design and topology optimization
Abstract Design optimization considering the presence of uncertainties in parameters poses
an extremely challenging problem. The source of difficulties comes with reliability-based …
an extremely challenging problem. The source of difficulties comes with reliability-based …
Sequential sampling approach to energy‐based multi‐objective design optimization of steel frames with correlated random parameters
This work presents a novel sequential sampling approach to the multi‐objective reliability‐
based design optimization of moment‐resisting steel frames subjected to earthquake …
based design optimization of moment‐resisting steel frames subjected to earthquake …
Model selection of Gaussian mixture process and its application
X Fu - Communications in Statistics-Theory and Methods, 2024 - Taylor & Francis
In this article, new penalized likelihood methods are proposed for model selection of
Gaussian mixture process. Our methods integrate functional principal component analysis …
Gaussian mixture process. Our methods integrate functional principal component analysis …
[PDF][PDF] Combined Gaussian process regression model and comprehensive learning particle swarm optimizer in reliability-based structural optimization
TH Van¹, B Do, S Limkatanyu, S Tangaramvong - sci-en-tech.com
Reliability-based design optimization (RBDO) addresses the cost-effective integrity design of
structures in the presence of inherent uncertain parameters. Processing this class of …
structures in the presence of inherent uncertain parameters. Processing this class of …