Table 13 Results of comparison with other algorithms for functions F1; F6; F7; F10; F12; F13; F15; F16 and F18.

From: Improved optimization based on parrot’s chaotic optimizer for solving complex problems in engineering and medical image segmentation

Algorithms

Metric

F1

F6

F7

F10

F12

F13

F15

F16

F18

CPO-10

Mean

0

−0.5

−0.007819

−1.9004e−16

−1

0.98241

0.16758

0.31141

−0.5

Std

0

1.0324e−05

0.004367

1.4285e−16

1.8521e−05

0.082809

0.039318

0.56745

0.70711

GWO

Mean

−2.0396e−31

−0.40009

−0.00045389

−1.8411e−15

−0.80726

0.88586

−0.091484

0.31143

−0.50008

Std

4.7834e−31

0.20321

0.033501

2.2201e−14

0.39442

0.29896

0.27933

0.56742

0.70701

WOA

Mean

−4.6298e−79

−0.47544

−0.0022558

−2.1697e−16

−0.83032

0.87284

0.12501

0.31141

−0.50016

Std

2.4819e−78

0.10991

0.0024174

9.6295e−16

0.35937

0.31428

0.056061

0.56744

0.70697

GOA

Mean

8.3076e−57

−0.48292

0.0011084

−1.6422e−16

−0.93024

0.91824

0.1606

−0.31141

−0.5

Std

3.0837e−56

0.062912

0.037178

1.3666e−15

0.17902

0.134

0.036389

0.56745

0.70711

SCA

Mean

−0.0095457

−0.21952

−0.0091447

−0.033769

−0.14077

0.39859

−3.1865

−0.30897

−0.5001

Std

0.043434

0.75013

0.088573

0.16921

4.5825

4.3306

2.5057

0.56594

0.70728

COOT

Mean

1.4761e−37

−0.50189

−0.008021

2.8761e−17

−0.12333

0.95699

1.3279

−0.31141

−0.5

Std

2.201e−36

0.091001

0.036652

2.5686e−16

1.9339

0.38602

1.1549

0.56745

0.70711

PLO

Mean

1.1452e−20

−0.49956

0.000730

1.7378e−16

−1.0016

1.0001

0.2742

−0.31141

2.7083

Std

9.3233e−20

0.003862

0.004870

8.0064e−17

0.00803

0.09283

0.10837

0.56745

0.61277

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