Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction-Reference-Cited by-同舟云学术

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Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction

Published:2024-06 Issue:6 Volume:11 Page:1331-1341
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Zhang Zhiming¹^ORCID,Gao Shangce¹^ORCID,Zhou MengChu²^ORCID,Yan Mengtao³^ORCID,Cao Shuyang⁴^ORCID

Affiliation:

1. Faculty of Engineering, University of Toyama,Toyama,Japan,930-8555

2. New Jersey Institute of Technology,Helen and John C. Hartmann Department of Electrical and Computer Engineering,Newark,NJ,USA,07102

3. Gaoling School of Artificial Intelligence, Renmin University of China,Beijing,China,100872

4. College of Civil Engineering, Tongji University,Shanghai,China,200092

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570654/10539265/10539351.pdf?arnumber=10539351

Reference57 articles.

1. Deep learning velocity signals allow quantifying turbulence intensity

2. Comparison of 2D and 3D Electromagnetic Approaches to Predict Tropospheric Turbulence Effects in Clear Sky Conditions

3. Deep learning in fluid dynamics

4. Unsupervised deep learning for super-resolution reconstruction of turbulence

5. Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning

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1. Evolution and Role of Optimizers in Training Deep Learning Models;IEEE/CAA Journal of Automatica Sinica;2024-10

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