Data-driven approach to predict the fundamental period of steel-braced RC frames using stacked generalization machine learning models
Author:
Funder
World University of Bangladesh, Bangladesh
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00914-9.pdf
Reference46 articles.
1. Ahiwale, D., Kontoni, D.-P., & Darekar, P. (2023). Seismic performance assessment of reinforced concrete frames with different bracing systems. Innovative Infrastructure Solutions, 8, 1–18. https://doi.org/10.1007/s41062-023-01071-3
2. Ahmed, N. Z., Osama, M., & Attia, W. (2022). Prediction of the fundamental period of vibration of braced frame systems in irregular steel buildings. Cogent Engineering, 9(1), 2122183. https://doi.org/10.1080/23311916.2022.2122183
3. Aninthaneni, P. K., & Dhakal, R. P. (2017). Prediction of lateral stiffness and fundamental period of concentrically braced frame buildings. Bulletin of Earthquake Engineering, 15(7), 3053–3082. https://doi.org/10.1007/s10518-016-0081-7
4. ASCE 7-22. (2022). Minimum design loads for buildings and other structures. In ANSI/ASCE standard.
5. Aslay, S., & Dede, T. (2022). 3D cost optimization of 3 story RC constructional building using Jaya algorithm. Structures, 40, 803–811. https://doi.org/10.1016/j.istruc.2022.04.055
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2. Deep symbolic regression for numerical formulation of fundamental period in concentrically steel-braced RC frames;Asian Journal of Civil Engineering;2024-05-23
3. Deep Symbolic Regression for Numerical Formulation of Fundamental Period in Concentrically Steel-Braced RC Frames;2024-05-17
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