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Theory and Modern Applications

Table 8 Approximate solutions for the temperature profile of a non-Newtonian fluid obtained by the LeNN-GNDO-SQP algorithm for different cases of 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

η

Solutions

Absolute Errors

Case I

Case II

Case III

Case IV

Case I

Case II

Case III

Case IV

0.0

1

1

0.999998

0.999997

5.23E−11

4.09E−12

1.10E−09

9.76E−10

0.1

0.881513

0.841329

0.787860

0.713456

3.89E−10

1.68E−10

2.47E−09

1.04E−08

0.2

0.764546

0.688382

0.587179

0.462278

7.12E−11

7.72E−10

1.30E−08

3.66E−08

0.3

0.650527

0.546120

0.410369

0.269040

3.31E−10

5.69E−10

9.47E−10

6.91E−08

0.4

0.540685

0.418361

0.266851

0.138775

8.57E−11

1.95E−11

8.14E−09

7.51E−08

0.5

0.435956

0.307555

0.160306

0.062423

3.20E−10

5.29E−10

4.44E−09

3.25E−08

0.6

0.336948

0.214699

0.088334

0.024060

5.85E−11

3.30E−11

4.15E−11

1.00E−10

0.7

0.243941

0.139411

0.044172

0.007830

2.25E−10

5.54E−10

3.41E−09

3.04E−08

0.8

0.156936

0.080150

0.019412

0.002121

1.85E−10

7.64E−10

2.98E−09

7.16E−08

0.9

0.075730

0.034578

0.006487

0.000437

1.37E−11

1.29E−10

9.14E−10

2.72E−08

1.0

1.25E−07

6.00E−10

4.33E−08

−5.33E − 07

1.65E−13

4.10E−12

1.27E−10

5.62E−10