Numerical Comparison and Analysis of Influencing Factors of PINNs in Inversion Calculation
Physical Information Neural Networks(PINNs)are widely used in numerical solution of differential equations and parameter estimation due to their powerful function expression ability,but the setting of hyperparameters and the choice of network architecture can affect the computational performance.A series of numerical calculations are conducted by taking the Navier-Stokes equation as an example to investigate the influencing factors of PINNs in the inversion calculation of nonlinear partial differential equations(PDE),and methods are found to improve the accuracy and computational efficiency of PINNs.
PINNsinversion calculationNavier-Stokes equationsanalysis of influencing factors
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