Estimating Seismic Behavior of Buckling-Restrained Braced Frames Using Machine Learning Algorithms

Author:

Kazemi Farzin,Mohebi Benyamin,Asgarkhani Neda

Publisher

Springer Nature Switzerland

Reference28 articles.

1. Yahyazadeh, A., Yakhchalian, M.: Probabilistic residual drift assessment of SMRFs with linear and nonlinear viscous dampers. J. Constr. Steel Res. 148, 409–421 (2018)

2. Kazemi, F., Mohebi, B., Yakhchalian, M.: Predicting the seismic collapse capacity of adjacent structures prone to pounding. Can. J. Civ. Eng. 47(6), 663–677 (2020)

3. Kazemi, F., Mohebi, B., Jankowski, R.: Predicting the seismic collapse capacity of adjacent SMRFs retrofitted with fluid viscous dampers in pounding conditions. Mech. Syst. Signal Process. 161, 107939 (2021)

4. Asgarkhani, N., Kazemi, F., Jankowski, R.: Optimal retrofit strategy using viscous dampers between adjacent RC and SMRFs prone to earthquake-induced pounding. Arch. Civ. Mech. Eng. 23(1), 1–26 (2023)

5. Kazemi, F., Asgarkhani, N., Manguri, A., Jankowski, R.: Investigating an optimal computational strategy to retrofit buildings with implementing viscous dampers. In: International Conference on Computational Science, pp. 184–191. Springer, Cham (2022)

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