Table 5 Design-matrix for observed and ANN predicted values for % burn-out.

From: A machine learning approach for significant utilization of high-ash Indian coals by metal chloride modification

Sl. No.

P. Time

Cat. conc.

P. Temp.

Observed % BO

Predicted % BO

1

30

9

610

68.13

68.63

2

30

6

510

44.18

43.65

3

10

3

610

27.36

27.22

4

20

3

510

22.86

23.93

5

10

9

710

55.31

55.36

6

20

6

510

29.61

27.37

7

30

6

710

71.18

69.52

8

30

3

610

60.48

62.70

9

20

6

710

63.42

63.79

10

20

9

710

69.22

66.87

11

10

3

510

15.95

19.56

12

10

6

710

46.36

47.54

13

10

6

610

31.00

30.60

14

20

3

610

46.11

44.75

15

30

6

610

67.95

66.47

16

20

9

510

33.69

32.38

17

30

9

710

72.12

70.30

18

30

9

510

49.72

51.60

19

10

9

510

20.79

22.48

20

30

3

710

70.88

67.168

21

20

6

610

52.31

52.175

22

10

9

610

32.65

34.678

23

10

6

510

18.23

22.702

24

20

3

710

56.84

58.017

25

20

9

610

54.33

57.35

26

10

3

710

40.65

39.133

27

30

3

510

33.76

37.14