Table 2 Comparative evaluation of the results achieved using the FGTO algorithm and other algorithms examined in the study.

From: Optimizing electric load forecasting with support vector regression/LSTM optimized by flexible Gorilla troops algorithm and neural networks a case study

Function

Mean/StD

SSA 20

BOA 21

BBO 22

LS 23

JSO 24

FGTO

F1

Mean

14.04

280.14

15.99

13.41

10.75182

0.00

StD

9.59

133.27

8.42

13.03

7.133238

0.00

F2

Mean

84.56

58.72

85.48

94.92

58.63184

49.15

StD

30.44

48.72

43.63

44.69

22.86165

34.93

F3

Mean

10.41

27.13

0.05

16.41

0.041065

0.05

StD

6.50

11.36

0.01

7.59

0.009138

0.01

F4

Mean

12.93

6.73

0.46

13.04

0.322247

0.31

StD

1.99

1.07

0.17

2.04

0.137248

0.12

F5

Mean

2.01

7.14

0.01

1.67

0.008556

0.01

StD

1.06

1.38

0.00

1.36

0

0.00

F6

Mean

1.45

1.06

0.00

1.60

0

0.00

StD

2.41

1.71

2.17

2.60

1.412479

1.52

F7

Mean

1.45

1.18

1.02

1.94

0.833979

1.01

StD

0.32

0.17

0.26

0.21

0.148508

0.20

F8

Mean

15.94

15.41

21.25

15.73

11.85482

14.68

StD

5.96

5.69

5.77

4.27

3.562759

4.15

F9

Mean

2.12

37.71

0.00

2.73

0

0.00

StD

2.03

12.60

0.00

1.70

0

0.00

F10

Mean

14.16

12.82

4.20

15.09

3.195383

2.30

StD

5.87

5.85

7.73

8.51

5.299867

7.85

F11

Mean

0.48

0.19

0.01

0.43

0.009413

0.01

StD

0.13

0.07

0.00

0.09

0

0.00

F12

Mean

0.00

0.00

0.00

0.00

0

0.00

StD

0.00

0.00

0.00

0.00

0

0.00

F13

Mean

1.55E-10

1.96E-03

1.06E-03

3.25E-01

1.53E-10

1.42E-10

StD

2.30E-11

5.62E-02

5.27E-02

2.45E-01

1.85E-11

1.47E-11

F14

Mean

1.07E + 00

2.35E + 00

2.02E + 00

2.25E + 00

0.874596

9.26E-01

StD

2.74E-01

1.43E + 00

1.11E + 00

1.53E + 00

0.240014

2.42E-01

F15

Mean

1.34E-04

7.42E-04

2.14E-03

3.55E-03

0.0001

1.20E-04

StD

3.15E-03

1.31E-02

2.06E-02

6.31E-02

0.002556

1.91E-03

F16

Mean

-5.07E-01

-6.85E-01

-7.78E-01

-7.63E-01

-0.63141

-7.21E-01

StD

5.91E-05

1.79E-04

1.93E-04

1.45E-04

5.67E-05

5.03E-05

F17

Mean

2.73E-01

2.32E-01

2.53E-01

2.03E-01

0.146912

1.76E-01

StD

1.42E-03

1.78E-08

2.90E-08

4.80E-03

1.54E-08

1.17E-08

F18

Mean

1.85E + 00

1.91E + 00

1.70E + 00

3.01E + 00

1.695975

1.17E + 00

StD

6.72E-14

2.72E-08

3.29E-08

1.74E + 00

6.44E-14

4.13E-14

F19

Mean

-2.43E + 00

-2.72E + 00

-2.54E + 00

-3.49E + 00

-2.68709

-2.14E + 00

StD

2.40E-15

4.00E-08

4.05E-08

2.68E-02

1.97E-15

1.91E-15

F20

Mean

-2.68E + 00

-1.58E + 00

-2.56E + 00

-2.34E + 00

-2.17715

-1.96E + 00

StD

2.72E-02

1.70E-01

2.86E-08

2.10E-01

2.45E-08

2.73E-08

F21

Mean

-6.67E + 00

-4.12E + 00

-3.87E + 00

-5.89E + 00

-6.13097

-4.04E + 00

StD

1.13E + 00

1.34E + 00

9.47E-01

1.23E + 00

0.711617

8.11E-01

F22

Mean

-7.37E + 00

-7.42E + 00

-6.06E + 00

-5.60E + 00

-6.84894

-6.50E + 00

StD

3.92E-01

1.26E + 00

6.66E-01

3.43E-01

0.341275

2.35E-01

F23

Mean

-5.41E + 00

-4.42E + 00

-4.57E + 00

-8.13E + 00

-6.21393

-6.67E + 00

StD

6.96E-01

7.47E-01

8.63E-01

7.98E-01

0.658112

6.27E-01