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Theory and Modern Applications

Table 10 Performance of fitness function and performance measures (MAD,TIC and RMSE) obtained during 100 independent runs by the proposed algorithm for problem 2

From: Application of Legendre polynomials based neural networks for the analysis of heat and mass transfer of a non-Newtonian fluid in a porous channel

Fit

MAD

TIC

RMSE

Min

Mean

Std

Min

Mean

Std

Min

Mean

Std

Min

Mean

Std

7.88E−11

4.84E−08

1.34E−07

5.33E−05

8.42E−04

6.43E−04

2.30E−05

3.68E−04

2.78E−04

6.12E−05

9.80E−04

7.41E−04

1.61E−10

3.46E−07

4.97E−07

3.10E−04

7.39E−03

5.93E−03

1.56E−04

3.95E−03

3.18E−03

3.51E−04

8.72E−03

7.00E−03

1.73E−09

2.79E−06

7.43E−06

1.39E−03

9.10E−03

7.54E−03

1.01E−03

6.39E−03

4.75E−03

1.82E−03

1.17E−02

9.29E−03

1.63E−08

8.20E−06

1.80E−05

7.95E−04

1.94E−02

1.04E−02

7.59E−04

1.68E−02

8.43E−03

1.09E−03

2.60E−02

1.38E−02