Prof. Dr. Flavius Guias

F. Guias, “Epidemic models with several levels of immunity,” in Quantitative demography and health estimates, Cham: Springer, 2023, pp. 163–174.

F. Guias, “Stochastic Runge-Kutta Solvers Based on Markov Jump Processes and Applications to Non-autonomous Systems of Differential Equations,” in Data analysis and related applications, 1, London ; Hoboken, NJ: John Wiley & Sons, 2022, pp. 199–206.

F. Guias, “Stochastic Picard-Runge-Kutta solvers for large systems of autonomous ordinary differential equations,” in 2017 fourth International Conference on Mathematics and Computers in Science and Industry - MCSI 2017 : Corfu, Greece, 24-27 August 2017 : proceedings, Piscataway, NJ: IEEE, 2017, pp. 289–302.

F. Guias, “A numerical method for ordinary differential equations based on adaptive time steps of Markov jump processes,” in Proceedings of the international conference of numerical analysis and applied mathematics ICNAAM 2021, 2023.

F. Guias, “Equilibrium Solutions of a Modified SIR Model with Vaccination and Several Levels of Immunity,” WSEAS Transactions on Systems and Control, vol. 18, pp. 550–560, 2023 [Online]. Available: https://wseas.com/journals/sac/2023/b165103-036(2023).pdf

F. Guias, “On efficacy and effectiveness of vaccines,” Spora : a journal of biomathematics, vol. 8 (2022), pp. 56–60, 2022.

F. Guias, “Numerical simulation of a modified SIR model fitting statistical data for COVID-19,” WSEAS transactions on computer research, vol. 8 (2020), pp. 115–125, 2020.

F. Guias, “Effects of the reproduction number in a SEIIRD model describing the time evolution of COVID-19 at country level,” WSEAS transactions on computer research, vol. 19 (2020), pp. 292–297, 2020.

F. Guias, “Numerical solvers for large systems of ordinary differential equations based on the stochastic direct simulation method improved by the Picard and Runge-Kutta principles,” International journal of mathematics and computers in simulation, vol. 11 (2017), pp. 93–99, 2017.

F. Guias and P. Eremeev, “Improving the stochastic direct simulation method with applications to evolution partial differential equations,” Applied mathematics and computation, no. 289, pp. 353–370, 2016.