SIRG-BSU_1.pdf
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This document appears to be a lecture on soft computing given by Dr. Ahmed Elngar. It introduces soft computing and discusses its main goals of developing intelligent machines and solving nonlinear problems that cannot be modeled mathematically. Examples provided include using evolutionary computation to solve a money allocation problem and fuzzy logic to control robot movement. The lecture aims to evaluate IoT performance by proposing a secure architecture to address security issues in educational IoT systems.
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SIRG-BSU_1.pdf
- 1. Lecture – 01 Introduction to soft computing Dr. Ahmed Elngar Associate Professor Head of Computer Science Department Faculty of Computers and Artificial Intelligence Beni-Suef University Faculty of Computers and Information Technology, American University in the Emirates 1 Dr. Ahmed Elngar 10/17/2023
- 4. 1.1 What is computer vision? 4 10/17/2023
- 5. 5 10/17/2023
- 6. 6 10/17/2023
- 7. Cont.. 7 • Many more 10/17/2023
- 8. Soft computing 8 Soft computing could therefore be seen as a series of techniques and methods so that real practical situations could be dealt with in the same way as humans deal with them, i.e. on the basis of intelligence, common sense, consideration of analogies, approaches, etc. 10/17/2023
- 9. 9 10/17/2023
- 10. 10 10/17/2023
- 11. 11 The main goal of Soft Computing The main goal of Soft Computing is to develop intelligent machines and to solve nonlinear and mathematically unmodelled system problems (Zadeh 1994) and (Zadeh 2001). The applications of Soft Computing have proved two main advantages. First, it made solving nonlinear problems, in which mathematical models are not available, possible. Second, it introduced human knowledge such as cognition, recognition, understanding, learning, and others into the fields of computing. This resulted in the possibility of constructing intelligent systems such as autonomous self-tuning systems, and automated designed systems. 10/17/2023
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- 14. 14 10/17/2023
- 15. 15 10/17/2023
- 16. 16 10/17/2023
- 17. 17 Example : Money allocation problem (Evolutionary Computation) 10/17/2023
- 18. 18 Example : Robot movement (Fuzzy Logic) 10/17/2023
- 19. 19 10/17/2023
- 20. 20 10/17/2023
- 21. 21 10/17/2023
- 22. 22 10/17/2023
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- 24. 24 10/17/2023
- 26. Aim of our Research Group: 26 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. 10/17/2023
- 27. Thanks and Acknowledgement Thank you 27 10/17/2023