Studies on infectious viruses have been conducted over a long period of time to understand their transmission and characteristics of variation, to gain a lot of knowledge such as testing methods and treatment measures, and to develop various vaccines.
The world’s danger of contagion still continues to spread, and the reality implies that viruses need to be more deeply studied.
One of the problems is the prediction of virus transmission by mathematical modeling. This research based on mathematical modeling has been widely conducted in the world, running up to thousands of pieces.
Mathematical modeling makes it possible to predict future transmission situations and to predict the number of medical personnel, beds, medical equipment, medical drug supplies, etc. that hospitals need to prepare. It can also simulate and find a rational approach for health care.
Kim Ju Hyong, a researcher at the Faculty of Biomedical Engineering, proposed a genetic algorithm method to determine the unknown parameters involved in the mathematical model that describes the transmission of virus infection, one of the global optimization calculation methods.
To test the validity of this method, he built a SEIHRD model and compared the accuracy of the simulation with the determination results of unknown parameters when the underlying data were prepared in various forms.
For further details, please refer to his paper “A Method to Determine the Unknown Parameters of Mathematical Model of Epidemic Transmission by Genetic Algorithm” in “Proceedings of KUTIC-2025”.