Prediction of aerodynamic flow fields using convolutional neural networks-Reference-Cited by-同舟云学术

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Prediction of aerodynamic flow fields using convolutional neural networks

Published:2019-06-12 Issue:2 Volume:64 Page:525-545
ISSN:0178-7675
Container-title:Computational Mechanics
language:en
Short-container-title:Comput Mech

Author:

Bhatnagar Saakaar,Afshar Yaser,Pan Shaowu,Duraisamy Karthik,Kaushik Shailendra

Funder

NSF

General Motors Corporation

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Mathematics,Computational Theory and Mathematics,Mechanical Engineering,Ocean Engineering,Computational Mechanics

Link

http://link.springer.com/content/pdf/10.1007/s00466-019-01740-0.pdf

Reference48 articles.

1. Aksoy S, Haralick RM (2000) Feature normalization and likelihood-based similarity measures for image retrieval. Pattern Recognit Lett 22:563–582

2. Amidror I (2002) Scattered data interpolation methods for electronic imaging systems: a survey. J Electron Imaging 11(2):157–176

3. Aranake A, Lakshminarayan V, Duraisamy K (2012) Assessment of transition model and cfd methodology for wind turbine flows. In: 42nd AIAA fluid dynamics conference and exhibit. American Institute of Aeronautics and Astronautics, p 2720

4. Bengio Y (2009) Learning deep architectures for ai. Found Trends Mach Learn 2(1):1–127

5. Carr JC, Beatson RK, Cherrie JB, Mitchell TJ, Fright WR, McCallum BC, Evans TR (2001) Reconstruction and representation of 3d objects with radial basis functions. In: Proceedings of the 28th annual conference on computer graphics and interactive techniques. ACM, New York, NY, USA, SIGGRAPH ’01, pp 67–76

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