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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