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Table 8 Statistical error analysis of PINNs results 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

MAE

MSE

Range

Variance

Standard deviation

0.0

1.010e−05

1.207e−10

1.610e−05

4.870e−12

3.803e−06

0.1

1.128e−05

1.312e−10

1.875e−05

1.822e−11

4.269e−06

0.2

1.128e−05

1.386e−10

1.830e−05

1.965e−11

4.269e−06

0.3

1.184e−05

1.464e−10

1.896e−05

2.091e−11

4.433e−06

0.4

1.266e−05

1.617e−10

2.049e−05

2.257e−11

4.582e−06

0.5

1.341e−05

1.933e−10

2.256e−05

2.408e−11

4.823e−06

0.6

1.429e−05

2.029e−10

2.411e−05

2.575e−11

5.075e−06

0.7

1.497e−05

2.179e−10

2.642e−05

2.724e−11

5.309e−06

0.8

1.581e−05

2.339e−10

2.851e−05

2.883e−11

5.617e−06

0.9

1.581e−05

2.648e−10

2.942e−05

3.079e−11

5.689e−06

1.0

1.736e−05

2.716e−10

3.005e−05

3.237e−11

5.723e−06