%0 Journal Article
%T Optimal Control of Infectious Diseases Using the Artificial Neural Networks
%J Control and Optimization in Applied Mathematics
%I Payame Noor University (PNU)
%Z 2383-3130
%A Heydari Dastjerdi, Rasoul
%A Ahmadi, Ghasem
%A Dadkhah, Mahmood
%A Yari, Ayatollah
%D 2023
%\ 12/01/2023
%V 8
%N 2
%P 17-32
%! Optimal Control of Infectious Diseases Using the Artificial Neural Networks
%K Optimal control
%K Pontryagin's minimum principle
%K Artificial neural network
%K Epidemic model
%R 10.30473/coam.2023.64776.1208
%X This paper presents a novel approach using artificial neural networks to solve the SEIR (Susceptible, Exposed, Infected, and Recovered) model of infectious diseases based on dynamical systems. Optimal control techniques are employed to determine a vaccination schedule for a standard SEIR epidemic model. The multilayer perceptron is utilized to approximate the state and co-state functions of the SEIR model and to solve the optimal control problem by utilizing a nonlinear programming approach. By constructing a loss function and using Pontryagin's Minimum Principle (PMP) for the SEIR model, a minimization problem is defined, a minimization problem is defined, and the approximate solution of the Hamiltonian system is computed. This method is compared with the fourth-order Runge-Kutta method. The proposed approach's effectiveness is demonstrated through illustrative examples.
%U https://mathco.journals.pnu.ac.ir/article_9819_6a202a7bfca1e3d16da47c17ca790b96.pdf