Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Predicting shear capacity of rectangular hollow RC columns using neural networks
https://orcid.org/http://orcid.org/0000-0001-7696-3450
This study predicts the shear strength of rectangular hollow reinforced concrete (RC) columns using artificial neural network (ANN). A total of 120 experimental results are collected from literature and used for establishing the machine learning model. The results reveal that the proposed ANN model predicts the shear strength of rectangular hollow RC columns accurately with R2 of 0.99. Additionally, the relative importance of input parameters on the calculated shear strength of RC columns is evaluated using Shapley value. Based on the ANN model, a graphical user interface tool is also developed and readily used in predicting the shear strength of rectangular hollow RC columns.
Predicting shear capacity of rectangular hollow RC columns using neural networks
https://orcid.org/http://orcid.org/0000-0001-7696-3450
This study predicts the shear strength of rectangular hollow reinforced concrete (RC) columns using artificial neural network (ANN). A total of 120 experimental results are collected from literature and used for establishing the machine learning model. The results reveal that the proposed ANN model predicts the shear strength of rectangular hollow RC columns accurately with R2 of 0.99. Additionally, the relative importance of input parameters on the calculated shear strength of RC columns is evaluated using Shapley value. Based on the ANN model, a graphical user interface tool is also developed and readily used in predicting the shear strength of rectangular hollow RC columns.
Predicting shear capacity of rectangular hollow RC columns using neural networks
https://orcid.org/http://orcid.org/0000-0001-7696-3450
This study predicts the shear strength of rectangular hollow reinforced concrete (RC) columns using artificial neural network (ANN). A total of 120 experimental results are collected from literature and used for establishing the machine learning model. The results reveal that the proposed ANN model predicts the shear strength of rectangular hollow RC columns accurately with R2 of 0.99. Additionally, the relative importance of input parameters on the calculated shear strength of RC columns is evaluated using Shapley value. Based on the ANN model, a graphical user interface tool is also developed and readily used in predicting the shear strength of rectangular hollow RC columns.
Predicting shear capacity of rectangular hollow RC columns using neural networks
Asian J Civ Eng
Nguyen, Xuan-Bang (Autor:in) / Tran, Viet-Linh (Autor:in) / Phan, Huy-Thien (Autor:in) / Nguyen, Duy-Duan (Autor:in)
Asian Journal of Civil Engineering ; 25 ; 2509-2520
01.04.2024
12 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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