Modeling ground motion in Mexico City using artificial neural networks
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| Format: | Artículo científico |
| Language: | en |
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Universidad Nacional Autónoma de México
2003
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| _version_ | 1876478009037291520 |
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| author | Silvia R. García |
| author_facet | Silvia R. García |
| contents | Modeling ground motion in Mexico City using artificial neural networks Silvia R. García Miguel P. Romo Neftalí Sarmiento Ciencias de la Tierra Ground motion site response neural networks learning algorithms artificial intelligence After the September 1985 earthquakes in Mexico City, many strong motion instruments were laid down throughout theValley of Mexico. Since then, a wealth of valuable information has been gathered. This has provided an excellent opportunity todevelop 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 fromone multivariate space of information to another, given a set of data representing that mapping. Accordingly, research aimed atdeveloping an ANN to model the earthquake response of Mexico City soil deposits was initiated a few years ago. The resultingnetwork that allows the computation of the response of the clayey ground is presented and discussed in this paper. It is shown thatwell designed networks represent a genuine alternative to analytical methods. 2003 artículo científico 0016-7169 https://www.redalyc.org/articulo.oa?id=56842203 en http://www.redalyc.org/revista.oa?id=568 Geofísica Internacional application/pdf Universidad Nacional Autónoma de México Geofísica Internacional (México) Num.2 Vol.42 |
| format | Artículo científico |
| id | redalyc_56842203 |
| institution | Redalyc |
| language | en |
| publishDate | 2003 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Modeling ground motion in Mexico City using artificial neural networks Silvia R. García Ciencias de la Tierra Ground motion site response neural networks learning algorithms artificial intelligence Modeling ground motion in Mexico City using artificial neural networks Silvia R. García Miguel P. Romo Neftalí Sarmiento Ciencias de la Tierra Ground motion site response neural networks learning algorithms artificial intelligence After the September 1985 earthquakes in Mexico City, many strong motion instruments were laid down throughout theValley of Mexico. Since then, a wealth of valuable information has been gathered. This has provided an excellent opportunity todevelop 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 fromone multivariate space of information to another, given a set of data representing that mapping. Accordingly, research aimed atdeveloping an ANN to model the earthquake response of Mexico City soil deposits was initiated a few years ago. The resultingnetwork that allows the computation of the response of the clayey ground is presented and discussed in this paper. It is shown thatwell designed networks represent a genuine alternative to analytical methods. 2003 artículo científico 0016-7169 https://www.redalyc.org/articulo.oa?id=56842203 en http://www.redalyc.org/revista.oa?id=568 Geofísica Internacional application/pdf Universidad Nacional Autónoma de México Geofísica Internacional (México) Num.2 Vol.42 |
| title | Modeling ground motion in Mexico City using artificial neural networks |
| topic | Ciencias de la Tierra Ground motion site response neural networks learning algorithms artificial intelligence |
| url | https://www.redalyc.org/articulo.oa?id=56842203 |