The construction of a neural network proxy model for ship hull design based on multi-fidelity datasets and the parameter freezing strategy-Reference-Cited by-同舟云学术

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The construction of a neural network proxy model for ship hull design based on multi-fidelity datasets and the parameter freezing strategy

Published:2024-03-18 Issue:4 Volume:23 Page:270-280
ISSN:2046-4177
Container-title:Journal of Marine Engineering & Technology
language:en
Short-container-title:Journal of Marine Engineering & Technology

Author:

Ao Yu¹²,Li Shaofan²^ORCID,Li Yunbo¹³,Gong Jiaye³

Affiliation:

1. College Of Shipbuilding Engineering, Harbin Engineering University, Harbin, People's Republic of China

2. Department of Civil and Environmental Engineering, University of California, Berkeley, California, USA

3. Ocean Science and Engineering College of SMU, Shanghai Maritime University, Shanghai, People's Republic of China

Funder

China Scholar Council

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/20464177.2024.2330174

Reference30 articles.

1. Reynolds-Averaged Navier–Stokes Equations for Turbulence Modeling

2. Anderson JD, Wendt J. 1995. Computational fluid dynamics. Vol. 206. Springer.

3. An integrated-hull design assisted by artificial intelligence-aided design method

4. An artificial intelligence-aided design (AIAD) of ship hull structures

5. Artificial Intelligence Design for Ship Structures: A Variant Multiple-Input Neural Network-Based Ship Resistance Prediction

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