Concurrent surrogate model selection (COSMOS): optimizing model type, kernel function, and hyper-parameters
This paper presents an automated surrogate model selection framework called the
Concurrent Surrogate Model Selection or COSMOS. Unlike most existing techniques …
Concurrent Surrogate Model Selection or COSMOS. Unlike most existing techniques …
A regularization method for constructing trend function in Kriging model
Y Zhang, W Yao, S Ye, X Chen - Structural and Multidisciplinary …, 2019 - Springer
Kriging is a popular surrogate for approximating computationally expensive computer
experiments. When sample points are limited, it is difficult to identify the overall trend of the …
experiments. When sample points are limited, it is difficult to identify the overall trend of the …
A classification approach to efficient global optimization in presence of non-computable domains
Gaussian-Process based optimization methods have become very popular in recent years
for the global optimization of complex systems with high computational costs. These …
for the global optimization of complex systems with high computational costs. These …
Dual Kriging assisted efficient global optimization of expensive problems with evaluation failures
Y He, J Sun, P Song, X Wang - Aerospace Science and Technology, 2020 - Elsevier
The Kriging-based efficient global optimization (EGO) method has been applied successfully
in many aerospace engineering optimization problems. However, in those practical …
in many aerospace engineering optimization problems. However, in those practical …
A penalized blind likelihood Kriging method for surrogate modeling
Y Zhang, W Yao, X Chen, S Ye - Structural and Multidisciplinary …, 2020 - Springer
Surrogate modeling is commonly used to replace expensive simulations of engineering
problems. Kriging is a popular surrogate for deterministic approximation due to its good …
problems. Kriging is a popular surrogate for deterministic approximation due to its good …
Lasso Kriging for efficiently selecting a global trend model
I Park - Structural and Multidisciplinary Optimization, 2021 - Springer
Kriging has been more and more widely used as a method to construct surrogate models in
a variety of areas within the engineering field. The universal Kriging is less appealing than …
a variety of areas within the engineering field. The universal Kriging is less appealing than …
Remarks for scaling up a general gaussian process to model large dataset with sub-models
Gaussian process models (GPs) have proven to be effective to approximate expensive
responses (eg high-fidelity simulations and experiments) and widely used for industrial …
responses (eg high-fidelity simulations and experiments) and widely used for industrial …
Learning uncertainty using clustering and local gaussian process regression
Gaussian process models (GPs) have proven to be effective to approximate expensive
responses (eg high-fidelity simulations and experiments). The estimated uncertainty of GP …
responses (eg high-fidelity simulations and experiments). The estimated uncertainty of GP …
[HTML][HTML] A quantitative validation method of kriging metamodel for injection mechanism based on Bayesian statistical inference
D You, X Shen, Y Zhu, J Deng, F Li - Metals, 2019 - mdpi.com
A Bayesian framework-based approach is proposed for the quantitative validation and
calibration of the kriging metamodel established by simulation and experimental training …
calibration of the kriging metamodel established by simulation and experimental training …
Göçmen kuşlar optimizasyon algoritmasının paralel bilgisayarlarda uygulanması
A Tülek - 2019 - search.proquest.com
Bu tez çalışmasında, metasezgisel optimizasyon algoritmalarından biri olan Göçmen Kuşlar
Optimizasyon (GKO) algoritması paralel bilgisayarlarda uygulanarak Paralel Göçmen Kuşlar …
Optimizasyon (GKO) algoritması paralel bilgisayarlarda uygulanarak Paralel Göçmen Kuşlar …