Mean period prediction models for Mexican interplate and intermediate-depth intraslab earthquake ground motions

Abstract

The aim of this paper is to predict the mean period, Tm, as a measure of the frequency content of interplate and intermediate-depth intraslab earthquake ground motions recorded at rock sites due to subduction earthquakes in Mexico. For this purpose, both Ground Motion Prediction Models (GMPMs), which use a parametric regression, and Support Vector Machine (SVM) regression, a type of machine learning algorithm used for regression analysis, are employed in this investigation. Therefore, two databases which include 484 and 300 earthquake ground motions recorded during interplate and intraslab historical Mexican earthquakes were assembled in this study. It is shown that Tm estimates depend on the type of earthquake (i.e., interplate or intraslab). While the SVM regression yields the lowest total standard deviation in predicting Tm, the GMPM still yields an acceptable total standard deviation similar to that reported in other studies. A comparison of the GMPM for intraslab earthquakes in Mexico with another GMPMs for predicting Tm recently introduced in the literature showed differences, which suggests that GMPMs for predicting Tm should be developed for specific regions.