Modeling ground motion in Mexico City using artificial neural networks

After the September 1985 earthquakes in Mexico City, many strong motion instruments were laid down throughout the Valley of Mexico. Since then, a wealth of valuable information has been gathered. This has provided an excellent opportunity to develop new analytical procedures based on knowledge-based...

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Main Authors: Neftalí Sarmiento, Miguel P. Romo, Silvia R. García
Format: Article
Language:English
Published: Universidad Nacional Autónoma de México, Instituto de Geofísica 2003-05-01
Series:Geofísica Internacional
Subjects:
Online Access:http://www.geofisica.unam.mx/unid_apoyo/editorial/publicaciones/investigacion/geofisica_internacional/anteriores/2003/02/garcia.pdf
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author Neftalí Sarmiento
Miguel P. Romo
Silvia R. García
author_facet Neftalí Sarmiento
Miguel P. Romo
Silvia R. García
author_sort Neftalí Sarmiento
collection DOAJ
description After the September 1985 earthquakes in Mexico City, many strong motion instruments were laid down throughout the Valley of Mexico. Since then, a wealth of valuable information has been gathered. This has provided an excellent opportunity to develop new analytical procedures based on knowledge-based techniques.An Artificial Neural Network (ANN) is a computational mechanism able to acquire, represent, and compute a mapping from one multivariate space of information to another, given a set of data representing that mapping. Accordingly, research aimed at developing an ANN to model the earthquake response of Mexico City soil deposits was initiated a few years ago. The resulting network that allows the computation of the response of the clayey ground is presented and discussed in this paper. It is shown that well designed networks represent a genuine alternative to analytical methods.
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spelling doaj.art-d9b37179b68f4d29a5f2baf9b5260d422023-08-02T01:30:07ZengUniversidad Nacional Autónoma de México, Instituto de GeofísicaGeofísica Internacional0016-71692003-05-01422173183Modeling ground motion in Mexico City using artificial neural networksNeftalí SarmientoMiguel P. RomoSilvia R. GarcíaAfter the September 1985 earthquakes in Mexico City, many strong motion instruments were laid down throughout the Valley of Mexico. Since then, a wealth of valuable information has been gathered. This has provided an excellent opportunity to develop new analytical procedures based on knowledge-based techniques.An Artificial Neural Network (ANN) is a computational mechanism able to acquire, represent, and compute a mapping from one multivariate space of information to another, given a set of data representing that mapping. Accordingly, research aimed at developing an ANN to model the earthquake response of Mexico City soil deposits was initiated a few years ago. The resulting network that allows the computation of the response of the clayey ground is presented and discussed in this paper. It is shown that well designed networks represent a genuine alternative to analytical methods.http://www.geofisica.unam.mx/unid_apoyo/editorial/publicaciones/investigacion/geofisica_internacional/anteriores/2003/02/garcia.pdfGround motionsite responseartificial intelligenceneural networkslearning algorithms
spellingShingle Neftalí Sarmiento
Miguel P. Romo
Silvia R. García
Modeling ground motion in Mexico City using artificial neural networks
Geofísica Internacional
Ground motion
site response
artificial intelligence
neural networks
learning algorithms
title Modeling ground motion in Mexico City using artificial neural networks
title_full Modeling ground motion in Mexico City using artificial neural networks
title_fullStr Modeling ground motion in Mexico City using artificial neural networks
title_full_unstemmed Modeling ground motion in Mexico City using artificial neural networks
title_short Modeling ground motion in Mexico City using artificial neural networks
title_sort modeling ground motion in mexico city using artificial neural networks
topic Ground motion
site response
artificial intelligence
neural networks
learning algorithms
url http://www.geofisica.unam.mx/unid_apoyo/editorial/publicaciones/investigacion/geofisica_internacional/anteriores/2003/02/garcia.pdf
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