データ拡張技術を用いた変位場およびひずみ場の予測精度向上に関する研究

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Summary, etc.：: <p>In generating a surrogate model of CAE results using deep learning techniques, it is possible to predict the strain field using an automatic differ...

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Material Type: 記事
Title: データ拡張技術を用いた変位場およびひずみ場の予測精度向上に関する研究
Volume: 2024.37
0
Author/Editor: 豊吉巧也
Author Heading: 豊吉巧也
TOYOSHI Takuya
Publication Date: 2024
Publication Date (W3CDTF): 2024
Alternative Title: Study of improving the accuracy of displacement and strain field predictions using data augmentation techniques
Periodical title: 計算力学講演会講演論文集
The Proceedings of The Computational Mechanics Conference
No. or year of volume/issue: 2024.37 0
Volume: 2024.37
Issue: 0
Pages: OS-2215
ISSN (Periodical Title): 2424-2799
Alias of Author: TOYOSHI Takuya
Subject Heading: Data augmentation
Relative frequency
Displacement field prediction
Strain field
Deep learning
Target Audience: 一般
DOI: 10.1299/jsmecmd.2024.37.OS-2215
Access Restrictions: インターネット公開
Data Provider (Database): 科学技術振興機構 : J-STAGE
http://www.jstage.jst.go.jp