ConvLSTM Neural Networks for seismic event prediction in Chile

Alex Gonzalez Fuentes, Orietta Nicolis, Billy Peralta, Marcello Chiodi

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Predicting seismic risk is a challenging task in order to avoid catastrophic effects. In this work, two models based on Convolutional Network (CNN) and Long Short Term Memory (LSTM) networks are proposed to predict the seismic risk in Chile. In particular, a ConvLSTM and a Multi-column ConvLSTM network are used for the prediction of the average number of seismic events greater than 2,8 magnitude on the Richter scale, in the Chilean regions of Coquimbo and Araucania between the years 2010 and 2017. For this model, the values of the intensity function estimated through an ETAS model and the accumulated displacement prior to a the seismic events are used as inputs. In particular, given the spatial and temporal characteristics of the seismic data, matrices of size 20x20 of the last 20 days are considered to predict the average number of seismic events of the next day in a given area. From the results obtained, the Multi-column ConvLSTM network achieved a coefficient of determination of 0,804 and a lower MSE than other networks.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665412216
DOI
EstadoPublicada - 5 ago 2021
Evento28th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021 - Virtual, Lima, Perú
Duración: 5 ago 20217 ago 2021

Serie de la publicación

NombreProceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021

Conferencia

Conferencia28th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021
País/TerritorioPerú
CiudadVirtual, Lima
Período5/08/217/08/21

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Informática aplicada
  • Teoría de la decisión (miscelánea)
  • Gestión y sistemas de información
  • Ingeniería eléctrica y electrónica
  • Control y optimización
  • Modelización y simulación

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