To evaluate the seismic risk associated with infrastructures, site-specific seismic hazard studies are needed to be performed. Further, for nonlinear time history analysis, one requires broadband ground motion. In modern times using physics-based simulations (PBS) for deriving the ground motion for future earthquakes has got due consideration. The PBS helps in decreasing the uncertainties related to the hazard estimation compared to GMPEs. There is a certain threshold to the PBS methods with the limited computational facilities. Hence, certain hybrid methods are required to attain a Broadband spectra for the simulated ground motion. This study uses a new ANN-based model to generate broadband ground motion spectra using the low-frequency spectral acceleration from PBS, source, path, and site parameters as input variables.A detailed parametric study and performance evaluation was made to 1 Springer Nature 2021 L A T E X template 2 ANNHBB identify the optimal input parameters in conjunction with the best-suited ANN architecture. The performance of the ANN model is demonstrated for Iwate (Mw 6.9,2008) earthquake. We found that the predicted values from the developed ANN model are in good agreement with the recorded data. Furthermore, time histories are generated using the spectral ordinate matching technique from the estimated broadband spectra.

To evaluate the seismic risk associated with infrastructures, site-specific seismic hazard studies are needed to be performed. Further, for non-linear time history analysis, one requires broadband ground motion. In modern times using physics-based simulations (PBS) for deriving the ground motion for future earthquakes has got due consideration. The PBS helps in decreasing the uncertainties related to the hazard estimation compared to GMPEs. There is a certain threshold to the PBS methods with the limited computational facilities. Hence, certain hybrid methods are required to attain a Broadband spectra for the simulated ground motion. This study uses a new ANN-based model to generate broadband ground motion spectra using the low-frequency spectral acceleration from PBS, source, path, and site parameters as input variables. A detailed parametric study and performance evaluation was made to identify the optimal input parameters in conjunction with the best-suited ANN architecture. The performance of the ANN model is demonstrated for Iwate (\(M_w\) 6.9,2008) earthquake. We found that the predicted values from the developed ANN model are in good agreement with the recorded data. Furthermore, time histories are generated using the spectral ordinate matching technique from the estimated broadband spectra.