Journal ArticleDOI
Improving variable-fidelity surrogate modeling via gradient-enhanced kriging and a generalized hybrid bridge function
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TLDR
It is shown that the gradient-enhanced GHBF proposed in this paper is very promising and can be used to significantly improve the efficiency, accuracy and robustness of VFM in the context of aero-loads prediction.About:
This article is published in Aerospace Science and Technology.The article was published on 2013-03-01. It has received 313 citations till now. The article focuses on the topics: Surrogate model & Kriging.read more
Citations
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Journal ArticleDOI
Comparison of parallel infill sampling criteria based on Kriging surrogate model
Cong Chen,Jiaxin Liu,Pingfei Xu +2 more
TL;DR: In this paper , an adaptive distance function is proposed, which is used to avoid the concentration problem of update points and also improves the global search ability of the infill sampling criterion, and seven test problems were used to evaluate these criteria to verify the effectiveness of these methods.
Proceedings ArticleDOI
Surrogate-based Robust Airfoil Optimization under Aleatory Flight Condition and Geometric Uncertainties
Journal ArticleDOI
Multi-Fidelity Sparse Polynomial Chaos and Kriging Surrogate Models Applied to Analytical Benchmark Problems
TL;DR: Analytical benchmark problems are used to show that accurate multi-f fidelity surrogate models can be obtained at lower computational cost than high-fidelity models and leads to a more accurate and flexible method overall.
Journal ArticleDOI
Dynamically controlled variable-fidelity modelling for aircraft structural design optimisation
TL;DR: In this paper, the authors investigated dynamically controlled variable-fidelity modelling during aircraft conceptual design optimization, where fidelity is controlled as a dynamic parameter of the optimisation process, to promote early discovery of promising design characteristics prior to a detailed analysis of the best designs available.
Posted Content
EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions.
TL;DR: The EXPObench benchmark library as discussed by the authors provides an extensive comparison of six different surrogate algorithms on four expensive optimisation problems from different real-life applications, including hyperparameter tuning and simulation-based optimisation.
References
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Journal ArticleDOI
The design and analysis of computer experiments
TL;DR: This paper presents a meta-modelling framework for estimating Output from Computer Experiments-Predicting Output from Training Data and Criteria Based Designs for computer Experiments.
Journal ArticleDOI
Principles of geostatistics
TL;DR: In this article, the authors present a new science leading to such an approach, namely geostatistics, which is a new approach for estimating the estimation of ore grades and reserves.
Journal Article
A statistical approach to some basic mine valuation problems on the Witwatersrand
TL;DR: In this paper, the application of the lognormal curve to the frequency distribution of gold values is discussed, and some fundamental concepts in application of statistics to mine valuation on the Witwatersrand are discussed.
Journal ArticleDOI
Recent advances in surrogate-based optimization
TL;DR: The present state of the art of constructing surrogate models and their use in optimization strategies is reviewed and extensive use of pictorial examples are made to give guidance as to each method's strengths and weaknesses.
Journal ArticleDOI
A Trust Region Framework for Managing the Use of Approximation Models in Optimization
TL;DR: An analytically robust, globally convergent approach to managing the use of approximation models of varying fidelity in optimization, based on the trust region idea from nonlinear programming, which is shown to be provably convergent to a solution of the original high-fidelity problem.
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