Artículo
Pattern recognition to forecast seismic time series
Autor/es | Morales Esteban, Antonio
Martínez Álvarez, F. Troncoso Lora, Alicia Justo, J. L. Rubio Escudero, Cristina |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos Universidad de Sevilla. Departamento de Estructuras de Edificación e Ingeniería del Terreno |
Fecha de publicación | 2010 |
Fecha de depósito | 2022-12-01 |
Publicado en |
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Resumen | Earthquakes arrive without previous warning and can destroy a whole city in a few seconds, causing numerous deaths and
economical losses. Nowadays, a great effort is being made to develop techniques that forecast these ... Earthquakes arrive without previous warning and can destroy a whole city in a few seconds, causing numerous deaths and economical losses. Nowadays, a great effort is being made to develop techniques that forecast these unpredictable natural disasters in order to take precautionary measures. In this paper, clustering techniques are used to obtain patterns which model the behavior of seismic temporal data and can help to predict medium–large earthquakes. First, earthquakes are classified into different groups and the optimal number of groups, a priori unknown, is determined. Then, patterns are discovered when medium–large earthquakes happen. Results from the Spanish seismic temporal data provided by the Spanish Geographical Institute and non-parametric statistical tests are presented and discussed, showing a remarkable performance and the significance of the obtained results. |
Agencias financiadoras | Ministerio de Ciencia Y Tecnología (MCYT). España Junta de Andalucía |
Identificador del proyecto | BIA2004-01302
TIN-68084-C02 P07-TIC-02611 |
Cita | Morales Esteban, A., Martínez Álvarez, F., Troncoso Lora, A., Justo, J.L. y Rubio Escudero, C. (2010). Pattern recognition to forecast seismic time series. Expert Systems with Applications, 37 (12), 8333-8342. https://doi.org/10.1016/j.eswa.2010.05.050. |
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