Skip to main content

Table 9 The comparison of PINNs results with the exact solution for different values of time variable t to Example 4.2

From: A deep learning approach: physics-informed neural networks for solving a nonlinear telegraph equation with different boundary conditions

t

\(\text{ L}_{2}\)

\(\text{ L}_{\infty }\)

RMSE

0.0

\(6.051\times 10^{-6}\)

\(7.827\times 10^{-6}\)

\(4.268\times 10^{-6}\)

0.1

\(6.250\times 10^{-6}\)

\(7.816\times 10^{-6}\)

\(4.088\times 10^{-6}\)

0.2

\(6.248\times 10^{-6}\)

\(7.921\times 10^{-6}\)

\(3.790\times 10^{-6}\)

0.3

\(6.327\times 10^{-6}\)

\(7.775\times 10^{-6}\)

\(3.559\times 10^{-6}\)

0.4

\(6.497\times 10^{-6}\)

\(9.776\times 10^{-6}\)

\(3.390\times 10^{-6}\)

0.5

\(7.9402\times 10^{-6}\)

\(1.533\times 10^{-5}\)

\(3.746\times 10^{-6}\)