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Advances in Continuous and Discrete Models

Theory and Modern Applications

Table 12 Computational complexity analysis of the proposed algorithm for different cases of problems 1 and 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

Problem

Cases

Time (s) Fitness Evaluation

GNDO

SQP

LNN-GNDO-SQP

Mean

Std

Mean

Std

Mean

Std

I

I

1.148

0.887

0.522

7.05E−03

1.712

0.89405

II

1.051

0.388

0.532

3.68E−03

1.583

0.39168

III

2.271

0.945

0.643

8.06E−03

2.914

0.95306

IV

1.263

0.326

0.587

9.90E−03

1.85

0.3359

II

I

1.861

0.996

0.629

1.59E−02

2.49

1.0119

II

1.962

0.849

0.662

1.71E−02

2.624

0.8661

III

1.972

1.012

0.692

6.90E−03

2.664

1.0189

IV

2.025

1.107

0.652

5.66E−02

2.677

1.1636

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