Predicting the COVID-19 in the Metropolitan Region (Chile) using a GCN-LSTM neural network

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

Resumen

COVID-19 is considered one of the largest pandemics in recent times. Predicting the number of future COVID-19 cases is extremely important for governments in order to make decisions about mobility restrictions, and for hospitals to be able to manage medical supplies, as well as health staff. Most of the predictions of COVID-19 cases are based on mathematical-epidemiological models such as the SEIR and SIR models. In our work, we propose a model of neural networks GCN-LSTM (Graph Convolutional Network - Long Short Term Memory) to predict the spatio-temporal rate incidence of COVID-19 in the Metropolitana Region, Chile. While the GCN network incorporates the spatial correlation in the nearby municipalities, the LSTM network considers the temporal correlation for the prediction over time. To interpolate the missing daily data for the network input, the use of the GAM (Generalized Additive Model) model is proposed. The results show better predictions for some municipalities with higher habitat density.

Idioma originalInglés
Título de la publicación alojada2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665408738
DOI
EstadoPublicada - 2021
Evento2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021 - Virtual, Online, Chile
Duración: 6 dic. 20219 dic. 2021

Serie de la publicación

Nombre2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021

Conferencia

Conferencia2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021
País/TerritorioChile
CiudadVirtual, Online
Período6/12/219/12/21

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Redes de ordenadores y comunicaciones
  • Hardware y arquitectura
  • Sistemas de información
  • Gestión y sistemas de información
  • Ingeniería energética y tecnologías de la energía
  • Ingeniería eléctrica y electrónica
  • Control y optimización

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