Table 4 Central composite design (CCD) with experimental responses and predicted responses.

From: Optimization of ultrasound-aided extraction of bioactive ingredients from Vitis vinifera seeds using RSM and ANFIS modeling with machine learning algorithm

S.No

Parameters

Experimental value*

RSM prediction

ANFIS prediction

Machine learning algorithm prediction

X1

X2

X3

X4

X5

y1

y2

y3

y4

y5

y1

y2

y3

y4

y5

y1

y2

y3

y4

y5

y1

y2

y3

y4

y5

1

0.25

65

23

40

70

667.67

445.65

78.95

75.65

70.04

695.15

441.62

82.41

77.2256

72.3434

717

471

85.6

81.3

75.7

666.87

449.63

79.57

75.66

70.28

2

0.155

62.5

23

40

70

672.45

454.65

81.89

77.85

71.52

752.64

469.42

82.22

76.72

71.52

632

426

76.5

72.8

67.3

669.70

455.11

81.18

76.93

71.14

3

0.155

67.5

23

40

70

670.13

448.76

79.05

76.45

70.43

732.76

467.24

83.24

78.544

73.5081

634

427

76.8

73.3

67.8

668.34

451.40

79.52

76.10

70.49

4

0.155

65

23

40

67.5

658.65

463.34

80.34

73.78

70.37

751.71

472.56

82.26

77.4991

72.2171

635

427

76.7

73.1

67.6

662.44

458.40

80.11

74.71

70.42

5

0.155

65

23

40

72.5

659.67

462.34

81.32

74.71

70.24

735.34

465.39

83.61

78.0947

73.176

632

426

76.7

73

67.5

663.29

458.12

80.85

75.40

70.39

  1. *All the experiments repeated three times.