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Optimal Control of Infectious Diseases Using the Artificial Neural Networks | ||
Control and Optimization in Applied Mathematics | ||
مقاله 2، دوره 8، شماره 2، اسفند 2023، صفحه 17-32 اصل مقاله (516.28 K) | ||
نوع مقاله: Research Article | ||
شناسه دیجیتال (DOI): 10.30473/coam.2023.64776.1208 | ||
نویسندگان | ||
Rasoul Heydari Dastjerdi* ؛ Ghasem Ahmadi؛ Mahmood Dadkhah؛ Ayatollah Yari | ||
Department of Mathematics, Payame Noor University (PNU), P.O. BOX 19395-4697, Tehran, Iran. | ||
چکیده | ||
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. | ||
کلیدواژهها | ||
Optimal control؛ Pontryagin's minimum principle؛ Artificial neural network؛ Epidemic model | ||
مراجع | ||
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