Computationally Efficient Adaptive Design of Experiments for Global Metamodeling through Integrated Error Approximation and Multicriteria Search Strategies-Reference-Cited by-同舟云学术

Computationally Efficient Adaptive Design of Experiments for Global Metamodeling through Integrated Error Approximation and Multicriteria Search Strategies

Published:2023-08 Issue:8 Volume:149 Page:
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Yi Sang-ri¹^ORCID,Taflanidis Alexandros A.²^ORCID

Affiliation:

1. Postdoctoral Researcher, Dept. of Civil and Environmental Engineering, Univ. of California, Berkeley, CA 94720 (corresponding author). ORCID: .

2. Professor, Dept. of Civil and Environmental Engineering and Earth Sciences, Univ. of Notre Dame, Notre Dame, IN 46556. ORCID:

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

https://ascelibrary.org/doi/pdf/10.1061/JENMDT.EMENG-7083

Reference69 articles.

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3. Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model

4. Beyer K. J. Goldstein R. Ramakrishnan and U. Shaft. 1999. “When is nearest neighbor meaningful?” In Proc. Int. Conf. on Database Theory 217–235. Berlin: Springer.

5. An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis

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