Abstract
ABSTRACT In this study, a machine learning-based hybrid optimization method is developed to optimize tuned mass damper considering soil-structure interaction. A total of 200,000 time history analyses of the tuned mass damper-structure-soil system are conducted and the results are used to construct the database of six machine learning models. Three meta-heuristic algorithms are used for optimization. A weighted optimization algorithm is developed based on the three individual optimization algorithms. Compared with three individual optimization algorithms, the weighted optimization algorithm can achieve better optimization results. The robustness of the single ground motion-based optimization applied to other ground motions is also investigated.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
