日本建築学会構造系論文集
Online ISSN : 1881-8153
Print ISSN : 1340-4202
ISSN-L : 1340-4202
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
末長 大佑高瀬 裕也阿部 隆英折田 現太安藤 重裕
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2023 年 88 巻 806 号 p. 645-654

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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.

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