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Predicting shear capacity of rectangular hollow RC columns using neural networks

Nguyen, X.-B. and Tran, V.-L. and Phan, H.-T. and Nguyen, D.-D. (2023) Predicting shear capacity of rectangular hollow RC columns using neural networks. Asian Journal of Civil Engineering. ISSN 15630854

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Abstract

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. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Item Type: Article
Divisions: Offices > Office of International Cooperation
Identification Number: 10.1007/s42107-023-00924-7
Additional Information: cited By 0
URI: http://eprints.lqdtu.edu.vn/id/eprint/11045

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