#PINN

Hard Constraint Projection Boosts PINN Accuracy by an Order of Magnitude: Evidence from the Burgers Equation

Extending hard constraint projection (HCP) from linear PDEs to the nonlinear Burgers equation: a finite-difference projection matrix forces the PINN's final layer to strictly satisfy the governing equation, yielding data error about an order of magnitude lower than a standard PINN and greater robustness to collocation point selection.