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 random search for discrete robust design optimization of linear-elastic steel frames under interval parametric uncertainty
This study presents a new random search method for solving discrete robust design
optimization (RDO) problem of planar linear-elastic steel frames. The optimization problem …
optimization (RDO) problem of planar linear-elastic steel frames. The optimization problem …
Estimating Gaussian mixtures using sparse polynomial moment systems
The method of moments is a statistical technique for density estimation that solves a system
of moment equations to estimate the parameters of an unknown distribution. A fundamental …
of moment equations to estimate the parameters of an unknown distribution. A fundamental …
Optimum design of steel frames against progressive collapse by guided simulated annealing algorithm
B Tayfur, AT Daloglu - Steel and Composite Structures, 2024 - koreascience.kr
In this paper, a Guided Simulated Annealing (GSA) algorithm is presented to optimize 2D
and 3D steel frames against Progressive Collapse. Considering the nature of structural …
and 3D steel frames against Progressive Collapse. Considering the nature of structural …
[PDF][PDF] Learning General Gaussian Mixture Model with Integral Cosine Similarity.
Gaussian mixture model (GMM) is a powerful statistical tool in data modeling, especially for
unsupervised learning tasks. Traditional learning methods for GMM such as expectation …
unsupervised learning tasks. Traditional learning methods for GMM such as expectation …
Sequential mixture of Gaussian processes and saddlepoint approximation for reliability-based design optimization of structures
This paper presents an efficient optimization procedure for solving the reliability-based
design optimization (RBDO) problem of structures under aleatory uncertainty in material …
design optimization (RBDO) problem of structures under aleatory uncertainty in material …
Design optimization of adhesive-bonded FRP patches for repairing fatigue cracks in steel structures
This chapter presents the design optimization of adhesive-bonded fiber-reinforced polymer
(FRP) patches for repairing fatigue cracks in steel structures. The design optimization aims …
(FRP) patches for repairing fatigue cracks in steel structures. The design optimization aims …
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 …
Machine learning for extracting features of approximate optimal brace locations for steel frames
A method is presented for extracting features of approximate optimal brace types and
locations for large-scale steel building frames. The frame is subjected to static seismic loads …
locations for large-scale steel building frames. The frame is subjected to static seismic loads …
Characterizing Joint Distribution of Uncertainty Parameters and Production Forecasts Using Gaussian Mixture Model and a Two-Loop Expectation-Maximization …
G Gao, H Lu, C Blom - SPE Annual Technical Conference and …, 2024 - onepetro.org
Uncertainty quantification of reservoirs with multiple geological concepts and robust
optimization are key technologies for oil/gas field development planning, which require …
optimization are key technologies for oil/gas field development planning, which require …