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Abstract: Physics-informed neural networks (PINNs) offer a flexible framework for solving differential equations using physical constraints and data. This study focuses on second-order ...

The Backward Euler and Crank–Nicolson methods are solved using a tridiagonal solver implementing the Thomas algorithm. The first and last rows correspond to the boundary conditions, and the interior ...