Table 6 The results of UNI-M functions.

From: Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks

Algorithm

F1

F2

F3

F4

F5

F6

F7

IPM-GWO

AV

1.11E−13

1.42E−04

1.55E−03

1.99E−03

133.11

1.35E−03

0.0149

SD

6.11E − 06

1.01E−03

1.62E−06

1.87E−03

11.332

1.66E−03

0.040

 

p-value

0.039

0.026

0.0111

0.0111

0.0184

0.0184

0.032

MMI-GWO

AV

1.27E−19

1.17E−05

1.14E−02

1.65E−03

141.88

1.56E−03

0.0732

SD

6.11E − 06

1.25E−04

1.17E−03

1.44E−03

19. 253

1.45E−04

0.0033

 

p-value

0.026

0.033

0.0111

0.026

0.039

0.033

0.022

RGWO

AV

1.17E−29

1.11E18

1.11E−10

1.02E−08

50.33

1.13E−09

0.0655

SD

2.11E−18

1.02E−12

1.16E−10

1.03E−08

24.11

1.22E−09

0.0033

 

p-value

0.039

NA

0.0111

0.033

0.0077

0.022

0.026

GWO

AV

1.11E−14

2.11E−13

1.25E−05

1.11E−05

48.033

1.74E−08

0.111

SD

1.33E−09

1.11E−13

1.86E−05

1.11E−06

19.22

1.33E−09

0.0032

 

p-value

0.033

0.032

0.026

0.0184

0.017

0.039

0.032

CLGWO

AV

2.32E−17

3.16E−12

1.18E−06

1.25E−06

50.33

1.11E−09

0.1044

SD

3.33 E−16

1.44E−12

1.44E−06

1.41E−06

12.22

1.11E−09

0.0055

 

p-value

0.022

0.026

0.026

0.0184

0.039

0.0111

0.0184

CF-GWO

AV

1.28E33

1.32E−13

1.01E11

1.43E09

44.22

1.62E−10

0.039

SD

0.0000

1.33E18

1.22E11

1.01E09

9.26

1.33E−03

0.033

 

p-value

NA

0.022

NA

NA

NA

0.022

NA