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Mean period prediction models for Mexican interplate and intermediate-depth intraslab earthquake ground motions
https://orcid.org/0000-0002-7739-8489
Abstract The aim of this paper is to predict the mean period, T m, 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 T m estimates depend on the type of earthquake (i.e., interplate or intraslab). While the SVM regression yields the lowest total standard deviation in predicting T m, 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 T m recently introduced in the literature showed differences, which suggests that GMPMs for predicting T m should be developed for specific regions.
Highlights GMPM and SVM regression models are used for predicting T m for Mexican subduction earthquakes. T m estimates depends on the type of subduction earthquake (i.e., interplate or intraslab). SVM regression can be used as an alternative for traditional GMPMs for predicting T m.
Mean period prediction models for Mexican interplate and intermediate-depth intraslab earthquake ground motions
https://orcid.org/0000-0002-7739-8489
Abstract The aim of this paper is to predict the mean period, T m, 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 T m estimates depend on the type of earthquake (i.e., interplate or intraslab). While the SVM regression yields the lowest total standard deviation in predicting T m, 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 T m recently introduced in the literature showed differences, which suggests that GMPMs for predicting T m should be developed for specific regions.
Highlights GMPM and SVM regression models are used for predicting T m for Mexican subduction earthquakes. T m estimates depends on the type of subduction earthquake (i.e., interplate or intraslab). SVM regression can be used as an alternative for traditional GMPMs for predicting T m.
Mean period prediction models for Mexican interplate and intermediate-depth intraslab earthquake ground motions
https://orcid.org/0000-0002-7739-8489
Abstract The aim of this paper is to predict the mean period, T m, 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 T m estimates depend on the type of earthquake (i.e., interplate or intraslab). While the SVM regression yields the lowest total standard deviation in predicting T m, 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 T m recently introduced in the literature showed differences, which suggests that GMPMs for predicting T m should be developed for specific regions.
Highlights GMPM and SVM regression models are used for predicting T m for Mexican subduction earthquakes. T m estimates depends on the type of subduction earthquake (i.e., interplate or intraslab). SVM regression can be used as an alternative for traditional GMPMs for predicting T m.
Mean period prediction models for Mexican interplate and intermediate-depth intraslab earthquake ground motions
Ramos-Cruz, José M. (author) / Ruiz-García, Jorge (author)
2023-12-31
Article (Journal)
Electronic Resource
English
Ground Motion Correlations from Recorded Mexican Intermediate-depth, Intraslab Earthquakes
| Taylor & Francis Verlag | 2023
| Taylor & Francis Verlag | 2015