Forecasting of COVID-19 Cases Under Different Precaution Strategies in Turkey
Abstract
Keywords
COVID-19, Forecasting, ARIMA, Prophet, NARNN, Deep learning, LSTM
References
- [1] A. Rismanbaf, “Potential Treatments for COVID-19; a Narrative Literature Review,” Archives of academic emergency medicine, vol.8(1), 2020.
- [2] I. Rahimi, F. Chen, and A. H. Gandomi, “A review on COVID-19 forecasting models,” Neural Comput. Appl., vol. 35, pp.23671–23681, 2023.
- [3] I. Nesteruk, “Statistics based predictions of coronavirus 2019-nCoV spreading in mainland China,” medRxiv, 2020.
- [4] C. Anastassopoulou, L. Russo, A. Tsakris, and C. Siettos, “Data-based analysis, modelling and forecasting of the COVID-19 outbreak,” PLoS One, vol. 15, no. 3, pp. 1–21, 2020.
- [5] G. Giordano et al., “Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy,” Nat. Med., vol. 26, no. 6, pp. 855–860, 2020.
- [6] S. Moein et al., “Inefficiency of SIR models in forecasting COVID-19 epidemic: a case study of Isfahan,” Sci. Rep., vol. 11, no. 1, p. 4725, 2021.
- [7] İ. Kırbaş, A. Sözen, A. D. Tuncer, and F. Ş. Kazancıoğlu, “Comparative analysis and forecasting of COVID-19 cases in various European countries with ARIMA, NARNN and LSTM approaches,” Chaos, Solitons and Fractals, vol. 138, Sep. 2020.
- [8] T. Dehesh, H. A. Mardani-Fard, and P. Dehesh, “Forecasting of COVID-19 Confirmed Cases in Different Countries with ARIMA Models,” medRxiv ,2020.
- [9] D. Benvenuto, M. Giovanetti, L. Vassallo, S. Angeletti, and M. Ciccozzi, “Application of the ARIMA model on the COVID-2019 epidemic dataset,” Data Br., vol. 29, p. 105340, 2020.
- [10] M. Yousaf, S. Zahir, M. Riaz, S. M. Hussain, and K. Shah, “Statistical analysis of forecasting COVID-19 for upcoming month in Pakistan,” Chaos, Solitons & Fractals, vol. 138, p. 109926, 2020.