Extended Runge-Kutta Scheme and Neural Network Approach for SEIR Epidemic Model with Convex Incidence Rate

For solving first-order linear and nonlinear differential equations, a new two-stage implicit–explicit approach is given. The scheme’s first stage, or predictor implicit, while the second stage explicit. of proposed scheme an extended form existing Runge–Kutta scheme. stability consistency are also offered. In two phases, technique achieves third-order accuracy. method applied to SEIR epidemic model with convex incidence rate. local examined. evaluated compared Euler nonstandard finite difference methods. terms accuracy, produced plots show that suggested outperforms Furthermore, neural network being considered map relationship between time amount susceptible, exposed, infected people.