[Keynote] Machine Learning for Optimization of Planar Building Frames
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- Ohsaki Makoto
- Kyoto University
Bibliographic Information
- Other Title
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- [基調講演] 建築骨組最適化のための機械学習
Abstract
<p>Although machine learning tools such as neural network and support vector regression have been used as regression models of strustural responses, their application to structuructural optimization is rather new. In this presentation, levels of application of machine learning to structural optimization is classified, and requirements for successful application of machine learning is summarized. Three examples are shown for optimization of planar building frames. It is important for machine learning to be an effective tool for structural design, rather than a blackbox, that features independent of the size of frame should be identified.</p>
Journal
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- NCTAM papers, National Congress of Theoretical and Applied Mechanics, Japan
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NCTAM papers, National Congress of Theoretical and Applied Mechanics, Japan 66 (0), 135-, 2022
National Committee for IUTAM
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Details 詳細情報について
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- CRID
- 1390293788343053184
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed