Tendon Stress Estimation from Strain Data of a Bridge Girder Using Machine Learning-Based Surrogate Model.

Khayam, Sadia Umer; Ajmal, Ammar; Park, Junyoung; Kim, In-Ho; Park, Jong-Woong

Khayam, Sadia Umer; Ajmal, Ammar; Park, Junyoung; Kim, In-Ho; Park, Jong-Woong.

Afiliação

Khayam SU; Department of Civil and Environmental Engineering, Urban Design and Studies, Chung-Ang University, Seoul 06974, Republic of Korea.
Ajmal A; Department of Smart Cities, Chung-Ang University, Seoul 06974, Republic of Korea.
Park J; Department of Civil and Environmental Engineering, Urban Design and Studies, Chung-Ang University, Seoul 06974, Republic of Korea.
Kim IH; Department of Civil and Engineering, Kunsan National University, Kunsan 54150, Republic of Korea.
Park JW; Department of Civil and Environmental Engineering, Urban Design and Studies, Chung-Ang University, Seoul 06974, Republic of Korea.

Sensors (Basel) ; 23(11)2023 May 24.

Article em En | MEDLINE | ID: mdl-37299765

Assuntos

Aprendizado de Máquina; Tendões; Estresse Mecânico; Análise de Elementos Finitos

Palavras-chave

artificial neural network; dataset; finite element; machine learning; neural network; prestressed girder; sensors; tendons

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tendões / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article

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