COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain

COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain

Many types of research have been carried out with the aim of combating the COVID-19 pandemic since the first outbreak was detected in Wuhan, China. Anticipating the evolution of an outbreak helps to devise suitable economic, social and health care strategies to mitigate the effects of the virus. For...

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Bibliographic Details
Main Authors: Díaz-Lozano, M. (Author), Gómez-Orellana, A.M (Author), Guijo-Rubio, D. (Author), Gutiérrez, P.A (Author), Hervás-Martínez, C. (Author), Ortigosa-Moreno, L. (Author), Padillo-Ruiz, J. (Author), Romanos-Rodríguez, A. (Author), Túñez, I. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
Analytical procedure
Andalusia
Case-studies
COVID-19
COVID-19 contagion forecasting
Curve decomposition
Curves decomposition
Evolutionary artificial neural networks
Forecasting
Long-term forecasting
Neural networks
Polynomial approximation
Polynomial curve
Time series
Times series
Transmission rates
Viruses
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