HIGHLIGHTS
SUMMARY
There are structures, e_g masonry walls, or rocking bridge piers that may also exhibit rocking during an earthquake, while slender structures may rock on their foundation and/or overturn (Housner 1963; Ishiyama 1982; Yim et_al 1980; Yim and Chopra 1985). The rocking motion is a highly nonlinear problem since it involves a wide range of nonlinear physical phenomena, e_g impact, contact, uplift and sliding. The study discusses the use of supervised machine_learning (ML) algorithms to predict and/or classify the response of rigid blocks subjected to ground motions of different properties, e_g frequency content . . .
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