Shear bearing capacity prediction of STRC shear walls using data‐augmented fusion model

Machine learning (ML) accurately predicts the shear bearing capacity of steel tube‐reinforced concrete (STRC) shear walls, aiding optimization design. However, creating a database for STRC shear walls experimentally is time‐consuming and costly. The aim of this study is to propose a method for high‐...

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Veröffentlicht in:	Structural concrete : journal of the FIB 2024-08, Vol.25 (4), p.2609-2623
Hauptverfasser:	Yang, Guang‐chao, Zhang, Ji‐gang, Ma, Zhe‐hao, Xu, Wei‐xiao, Zhao, Guo‐liang, Song, Han‐yu
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Axial forces Back propagation networks Bearing capacity Data augmentation Design optimization fusion model Generative adversarial networks Machine learning Neural networks Numerical models Reinforced concrete Reinforcing steels shear bearing capacity Shear walls Steel tubes steel tube‐reinforced concrete shear walls
Online-Zugang:	Volltext
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