A. E. Kim

PARAMETRIZATION METHOD AND PHYSICS-INFORMED NEURAL NETWORKS FOR THE DUFFING EQUATION

Introduction. Physics-informed neural networks (PINNs) are increasingly proposed as universal solvers of differential equations, but their reliability for nonlinear oscillators with several periodic solutions is insufficiently studied. Aims and objectives. To compare D.S. Dzhumabaev’s parametrization method with PINNs...