Epidemic forecasting using mathematical modeling and machine learning methods
Keywords:
math modeling; epidemics; data analysis; machine learning; differential equationsAbstract
This research considers the construction of a mathematical model of an infectious disease epidemiс, finds a solution of the resulting system of ordinary differential equations by Runge-Kutta method, and approximates the function of process dynamics by machine learning from observed data. The aim of the study is to create a system for predicting the epidemic by mathematical modeling and machine learning methods.
References
Milik A., Prskawetz A., Feichtinger G., Sanderson W. C. Slow–wast dynamics in Wonderland, Envir.Modeling & Assessment, 1996. №1. P.3–17.
Slyusar V. On the Issue of Assessing the Effectiveness of Air Defense Based on a Pandemic Model, September 13, 2020.
Chen, Ricky T. Q., Rubanova Yulia, Bettencourt, Jesse and Duvenaud, David Neural Ordinary Differential Equations, 2018.
Clevert, Djork-Arné & Unterthiner, Thomas, Hochreiter, Sepp. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs), 2015.
Kingma, Diederik, Ba, Jimmy. Adam: A Method for Stochastic Optimization. International Conference on Learning Representations, 2014.
