Table 2 Neural network approximation for the coefficients
From: A novel computational approach to approximate fuzzy interpolation polynomials
t | \(x_0(t)\) | \(x_1(t)\) | \(x_2(t)\) | Error for FNN |
|---|---|---|---|---|
1 | −0.5915 | −2.5895 | −1.5784 | 2330.5296 |
2 | −0.9910 | −2.9033 | −1.9664 | 1896.6752 |
3 | −1.3356 | −3.3346 | −2.3696 | 999.56201 |
4 | −1.8050 | −3.8798 | −2.7561 | 401.56201 |
5 | −2.2257 | −4.1035 | −3.1100 | 95.188500 |
\(\vdots\) | \(\vdots\) | \(\vdots\) | \(\vdots\) | \(\vdots\) |
13 | −2.9996 | −4.9995 | −3.9996 | 0.86688366 |
14 | −2.9998 | −4.9996 | −3.9998 | 0.54635274 |
15 | −2.9999 | −4.9998 | −3.9999 | 0.23614301 |
16 | −3.0000 | −4.9999 | −4.0000 | 0.06896850 |
17 | −3.0000 | −5.0000 | −4.0000 | 0.02003805 |