Table 12 The rate of misclassification for additional datasets.

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

Classification models

MRD

MB

MBI

MRB

MRDBI

RI

Rectangle

Convex

CAE-264

9.66

2.48

15.50

10.90

45.23

21.54

1.21

N/A

PGBM + DN-167

N/A

N/A

12.26

6.07

36.75

N/A

N/A

N/A

TIRBM65

4.19

N/A

N/A

N/A

35.49

N/A

N/A

N/A

RandNet-266

8.48

1.24

11.64

13.48

43.70

17.01

0.08

5.44

ScatNet-263

7.50

1.26

18.39

12.29

50.50

8.03

0.01

6.49

LDANet-266

7.51

1.05

12.41

6.79

38.53

16.19

0.01

7.19

PCANet-2(softmax)66

8.51

1.41

11.54

6.84

35.85

13.40

0.50

4.20

SVM + Poly56

15.41

3.70

24.02

16.59

56.39

24.04

2.16

19.83

SVM + RBF56

11.09

3.02

22.59

14.60

55.17

24.03

2.16

19.09

DBN-356

10.29

3.12

16.29

6.72

47.40

22.49

2.59

18.64

NNet 56

18.09

4.70

27.39

20.03

62.17

33.19

7.15

32.24

SAA-3 [56]

10.29

3.45

23.01

11.30

51.92

24.11

2.39

18.39

EvoCNN69

5.21

1.05

4.52

2.49

35.03

5.12

0.01

4.82

IPFA

5.84

1.26

5.03

2.51

35.11

5.02

0.01

5.00

IPALO

6.89

1.42

5.76

2.90

37.63

5.11

0.02

5.69

IPPSO

6.00

1.31

5.11

2.63

36.99

5.09

0.01

5.33

IPCF-GWO1

4.93

1.08

4.49

2.49

35.12

4.48

0.01

5.01

IPCF-GWO2

5.21

1.11

5.01

3.12

37.22

5.01

0.02

5.22

IPCF-GWO3

4.99

1.09

4.59

2.49

35.04

5.26

0.01

5.11

IPCF-GWO4

5.14

1.21

5.22

3.21

36.22

5.00

0.02

5.32

IPCF-GWO5

6.03

1.11

5.31

4.12

39.21

5.21

0.02

5.21

IPCF-GWO6

5.99

1.20

4.92

2.99

36.00

5.80

0.01

5.01