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Table 7 The comparison of PINNs results with the exact solution for different values of time variable t to Example 4.1

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

\(6.114\times 10^{-7}\)

\(1.526\times 10^{-6}\)

\(5.976\times 10^{-7}\)

1.5

\(7.334\times 10^{-7}\)

\(1.800\times 10^{-6}\)

\(7.134\times 10^{-7}\)

2.5

\(8.764\times 10^{-7}\)

\(2.107\times 10^{-6}\)

\(8.476\times 10^{-7}\)

3.5

\(1.033\times 10^{-6}\)

\(2.429\times 10^{-6}\)

\(9.931\times 10^{-7}\)

4.5

\(1.223\times 10^{-6}\)

\(2.793\times 10^{-6}\)

\(1.165\times 10^{-6}\)

5.0

\(1.328\times 10^{-6}\)

\(2.982\times 10^{-6}\)

\(1.259\times 10^{-6}\)