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Table 1 Neural network approximation for the coefficients

From: A novel computational approach to approximate fuzzy interpolation polynomials

t \(x_0(t)\) \(x_1(t)\) \(x_2(t)\) \(x_3(t)\) Error for FNN
1 4.9018 6.9215 5.9307 7.9121 58,756.65
2 4.5321 6.6450 5.5480 7.6010 6479.790
3 4.0231 6.2056 5.1250 7.2212 1741.483
4 3.6850 5.8401 4.7851 6.7945 577.7597
5 3.2032 5.4001 4.3365 6.3330 210.8822
\(\vdots\) \(\vdots\) \(\vdots\) \(\vdots\) \(\vdots\) \(\vdots\)
15 2.0008 4.0007 3.0008 5.0006 0.366883
16 2.0007 4.0005 3.0006 5.0005 0.151818
17 2.0005 4.0004 3.0005 5.0003 0.062895
18 2.0004 4.0003 3.0004 5.0002 0.026075
19 2.0003 4.0002 3.0003 5.0001 0.010815