Forecasting Covid-19 Dynamics in Brazil: A Data Driven Approach
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- Fanelli, Duccio & Piazza, Francesco, 2020. "Analysis and forecast of COVID-19 spreading in China, Italy and France," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
- Michael te Vrugt & Jens Bickmann & Raphael Wittkowski, 2020. "Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
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- Mitsuyoshi Urashima & Katharina Otani & Yasutaka Hasegawa & Taisuke Akutsu, 2020. "BCG Vaccination and Mortality of COVID-19 across 173 Countries: An Ecological Study," IJERPH, MDPI, vol. 17(15), pages 1-20, August.
- Jelena Musulin & Sandi Baressi Šegota & Daniel Štifanić & Ivan Lorencin & Nikola Anđelić & Tijana Šušteršič & Anđela Blagojević & Nenad Filipović & Tomislav Ćabov & Elitza Markova-Car, 2021. "Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review," IJERPH, MDPI, vol. 18(8), pages 1-39, April.
- Emerson Vilar de Oliveira & Dunfrey Pires Aragão & Luiz Marcos Garcia Gonçalves, 2024. "A New Auto-Regressive Multi-Variable Modified Auto-Encoder for Multivariate Time-Series Prediction: A Case Study with Application to COVID-19 Pandemics," IJERPH, MDPI, vol. 21(4), pages 1-19, April.
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Keywords
time series prediction; Covid-19 pandemic; modified auto-encoder; data-driven;All these keywords.
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