Potential for Using Deep Learning for Digital-Twin System Validation Testing-Reference-Cited by-同舟云学术

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Potential for Using Deep Learning for Digital-Twin System Validation Testing

Published:2022-09-18 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC)
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Author:

Sherry Lance¹,Ansari Shamshad²,Baldo James³,Berlin Brett³,Shortle John⁴,Raz Ali⁴

Affiliation:

1. George Mason University,Center for Air Transportation Systems Research,Fairfax,Va.,USA,22030

2. Accure Inc.),Reston,Va.,USA

3. George Mason University,Data Analytics Engieering,Fairfax,Va.,USA,22031

4. George Mason University,System Engineering & Operations Research,Fairfax,Va.,USA,22030

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9925245/9925721/09925815.pdf?arnumber=9925815

Cited by 1 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. Towards Trajectory Conflict Prediction Using AI/ML For V&V Test Case Generation;2023 Integrated Communication, Navigation and Surveillance Conference (ICNS);2023-04-18

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