PREDICTION ACCURACY OF ENVELOPE CURVE FOR POST-INSTALLED ANCHORS BY MACHINE LEARNING WITH DECISION TREE AND NEURAL NETWORK
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- SUENAGA Daisuke
- Division of Sustainable Environmental Engineering, Muroran Institute of Technology
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- TAKASE Yuya
- College of Manufacturing and Design, Muroran Institute of Technology
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- ABE Takahide
- Institute of Technology, TOBISHIMA Corporation
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- ORITA Genta
- Institute of Technology, TOBISHIMA Corporation
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- ANDO Shigehiro
- Cement / Concrete laboratory, SUMITOMO OSAKA CEMENT Co., Ltd.
Bibliographic Information
- Other Title
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- 決定木とニューラルネットワークによる機械学習を用いたあと施工アンカーの包絡曲線の予測精度
Description
<p>Recently, artificial intelligence has been used in various fields, however researches of predicting load-displacement relationships for structural members are shortage. In this study, the shear force – shear displacement (Q -𝛿𝑆) relationships of post-installed anchors were predicted using machine learning with Decision Tree and Neural Network. As a result, the prediction results by Neural Network were the most accurate of the applied four methods. In addition, the prediction results of the Neural Network were compared with the evaluation results of the FEM analysis and Dowel model, which are the conventional methods. Finally, Neural Network was the most accurate algorism.</p>
Journal
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- Journal of Structural and Construction Engineering (Transactions of AIJ)
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Journal of Structural and Construction Engineering (Transactions of AIJ) 88 (806), 645-654, 2023-04-01
Architectural Institute of Japan
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Details 詳細情報について
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- CRID
- 1390577133276249856
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- ISSN
- 18818153
- 13404202
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
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- Abstract License Flag
- Disallowed