Identifying Suitable Ground Motion Prediction Equations for Taiwan Using New PGA Records in the Region: A Data-Driven Method

A ground motion prediction equation (GMPE) is an empirical model for predicting earthquake ground motions’ intensity measure [e.g., peak ground acceleration (PGA)]. In this study, we used 1,014 PGA records induced by three major earthquakes in Taiwan as the observation, on the basis to search for more suitable (PGA) GMPEs for the region from a GMPE database; the closer the observations and predictions are (or the greater the model’s likelihood function), the more the GMPE is recommended. Based on the likelihood functions calculated, this paper also introduces an objective, repeatable method to determine the logic-tree weights for GMPEs used in seismic hazard analyses, with the weights being proportional to the likelihood functions calculated based on observed ground motion records.