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Advances, Systems and Applications

Table 5 Performace comparison for throughput

From: QoS prediction in intelligent edge computing based on feature learning

TP

Matrix density=5%

Matrix density=10%

Matrix density=15%

Matrix density=20%

Methods

MAE

RMSE

MAE

RMSE

MAE

RMSE

MAE

RMSE

UPCC

29.4326

71.3528

22.3658

63.6902

20.8361

57.6302

18.1835

55.3903

IPCC

28.7652

62.4814

23.8052

60.1082

22.3727

58.2644

21.2426

56.9312

UIPCC

26.2808

60.8961

22.4295

54.7023

20.219

50.6028

18.9276

48.1629

DNM

18.4903

63.2993

16.2861

55.0821

15.1406

49.394

14.7933

48.4284

LAFIL

17.3753

55.46

14.692

48.552

13.7041

45.2544

12.8145

43.1456

MFAIN

16.0053

47.1833

12.5607

43.0931

11.9322

41.4552

11.4106

40.1253

Gains

7.90%

14.90%

14.50%

11.20%

12.90%

8.40%

11.00%

7.00%