Machine learning-based predictive models for equivalent damping ratio of RC shear walls

Energy-based seismic design is being rapidly developed and suggests that the seismic demands are met by the energy dissipation capacity of the structural members. Equivalent damping ratio is a measure of energy dissipation in structural members that accounts for the post-elastic behavior of the memb...

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Bibliographic Details
Published in:	Bulletin of earthquake engineering Vol. 21; no. 1; pp. 293 - 318
Main Authors:	Yaghoubi, Siamak Tahaei, Deger, Zeynep Tuna, Taskin, Gulsen, Sutcu, Fatih
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.01.2023 Springer Nature B.V
Subjects:	Algorithms Civil Engineering Cyclic loading Cyclic loads Damping Damping capacity Damping ratio Dependent variables Design Dynamic response Earth and Environmental Science Earth Sciences Earthquake dampers Earthquakes Elasticity Energy dissipation Energy exchange Environmental Engineering/Biotechnology Equivalence Gaussian process Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Hydrogeology Kernel functions Lateral forces Learning algorithms Machine learning Mechanical properties Model accuracy Modelling Original Article Performance evaluation Prediction models Regression Regression analysis Reinforced concrete Robustness (mathematics) Seismic activity Seismic design Seismic response Shear Stocks Structural engineering Structural Geology Structural members Gaussian process regression Reinforced concrete shear walls Equivalent damping ratio Machine learning
ISSN:	1570-761X, 1573-1456
Online Access:	Get full text
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