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Simulation Optimization for a Digital Twin Using a Multi-Fidelity Framework

  • Published:2021-12-12 Issue: Volume: Page:
  • ISSN:
  • Container-title:2021 Winter Simulation Conference (WSC)
  • language:
  • Short-container-title:

Author:

Cao Yiyun1,Currie Christine1,Onggo Bhakti Stephan1,Higgins Michael2

Affiliation:

1. Centre for Operational Research, Management Science and Information Systems, University of Southampton,Southampton,United Kingdom,SO17 1BJ

2. PowerTrain Manufacturing Engineering Ford Motor Company, Dunton Research Centre,Basildon,United Kingdom,SS15 6EE

Funder

Ford Motor Company

Publisher

IEEE

Cited by 6 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. Fast Prediction of Structural Stress Field Using Point Cloud Deep Learning;Mechanisms and Machine Science;2024

2. Tracking and Detecting Systematic Errors in Digital Twins;2023 Winter Simulation Conference (WSC);2023-12-10

3. The Use of Simulation with Machine Learning and Optimization for a Digital Twin-A Case on Formula 1 DSS;2022 Winter Simulation Conference (WSC);2022-12-11

4. Simulation: the Critical Technology in Digital Twin Development;2022 Winter Simulation Conference (WSC);2022-12-11

5. Multi-fidelity neural optimization machine for Digital Twins;Structural and Multidisciplinary Optimization;2022-11-16
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