FFNN

1. Lecture – 06
Introduction to soft computing
Dr. Ahmed Elngar
Faculty of Computers and Artificial Intelligence
Beni-Suef University
1
Dr. Ahmed Elngar
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2. Course Syllabus
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3. 3
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ANN (artificial neural network)

4. 4
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5. 5
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Network structure
Backpropagation Networks

6. 6
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7. 7
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8. 8
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9. 9
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10. 10
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11. 11
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12. 12
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13. 13
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14. 14
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15. 15
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16. 16
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17. 17
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18. 18
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19. 19
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20. 20
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21. 21
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22. 22
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23. 23
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24. 24
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25. 25
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26. 26
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27. 27
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28. 28
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29. 29
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30. 30
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31. 31
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32. 32
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33. 33
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Feed-forward Neural Network

34. 34
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35. 35
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Single layer- Feed-forward Neural Network

36. 36
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Feed-forward Neural Network

37. 37
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Feed-forward Neural Network

38. 38
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Multi Layer- Feed-forward Neural Network

39. 39
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Feed-forward Neural Network

40. 40
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Feed-forward Neural Network

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Feed-forward Neural Network

42. 42
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Difference between Feed-forward and Recurrent

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44. 44
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45. 45
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46. 46
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47. 47
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48. 48
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49. 49
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Number of nodes and layers

50. 50
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Settings

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Running and training NN

52. 52
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Running and training NN

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pruning

54. Aim of our Research Group:
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The aim of our Scientific Innovation research Group
(SIRG) to evaluate the IOT performance by propose a
secure architecture for the IoT security issues for
Education.
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55. Thanks and Acknowledgement
Thank you
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