Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion-Reference-Cited by-同舟云学术

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

Published:2017-01-02 Issue:1 Volume:59 Page:58-68
ISSN:0040-1706
Container-title:Technometrics
language:en
Short-container-title:Technometrics

Author:

He Xu¹,Tuo Rui¹,Wu C. F. Jeff²

Affiliation:

1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences 100190 Beijing, China ()

2. School of Industrial and Systems Engineering, Georgia Institute of Technology Atlanta, GA 30332 ()

Publisher

Informa UK Limited

Subject

Applied Mathematics,Modelling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00401706.2016.1142902

Reference23 articles.

1. A Connectionist Machine for Genetic Hillclimbing

2. Chkrebtii, O.A., Campbell, D.A., Girolami, M.A., and Calderhead, B. (2014), “Bayesian Uncertainty Quantification for Differential Equations,” http://arxiv.org/abs/1306.2365.

3. Multi-fidelity optimization via surrogate modelling

4. Nested orthogonal array-based Latin hypercube designs

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning-assisted discovery of flow reactor designs;Nature Chemical Engineering;2024-08-05

2. Active Learning for a Recursive Non-Additive Emulator for Multi-Fidelity Computer Experiments;Technometrics;2024-07-08

3. METHODOLOGY AND CHALLENGES OF SURROGATE MODELLING METHODS FOR MULTI-FIDELITY EXPENSIVE BLACK-BOX PROBLEMS;The ANZIAM Journal;2024-05-31

4. Conglomerate Multi-fidelity Gaussian Process Modeling, with Application to Heavy-Ion Collisions;SIAM/ASA Journal on Uncertainty Quantification;2024-05-30

5. Multi-fidelity data-driven design and analysis of reactor and tube simulations;Computers & Chemical Engineering;2023-11