Intelligent Systems

• 26 hrs lectures
• 26 hrs projects

• 60 pts final exam (written part)
• 40 pts projects

Students acquire knowledge of principles of intelligent systems and so they will be able to design these systems for solving of various practical problems.
A detailed overview of the current state of intelligent systems and the ability to use the acquired knowledge in their own research.

To give the students the knowledge of intelligent systems design (control, production, etc.) based on combinations of theories of neural networks, fuzzy sets, rough sets and genetic algorithms.

Intelligent systems are becoming an integral and important part of everyday life.

Basic knowledge of artificial intelligence in a scope of Fundamentals of Artificial Intelligence course of current study program at FIT. 

None.

• Mitchell, H. B.: Multi-Sensor Data Fusion, Springer-Verlag Berlin Heidelberg 2007, ISBN 978-3-540-71463-7
• Munakata,T.: Fundamentals of the New Artificial Intelligence, Springer, 2008, ISBN 978-1-84628-838-8
• Shi, Z.: Advanced Artificial Intelligence, World Scientific Publishing Co. Pte. Ltd., 2011, ISBN-13 978-981-4291-34-7
• Iba, H., Noman, N.: New Frontier in Evolutionary Algorithms, Imperial College Press, 2012, ISBN-13 978-1-84816-681-3
• Bramer, M.: Principles of Data Mining, Second edition, Springer-Verlag London 2013, ISBN 978-1-4471-4883-8
• Fraden, J.: Handbook of Modern Sensors, Springer  Springer International Publishing, 2016, ISBN 978-3-319-19302-1
• Kruse, R., Borgelt, Ch., Braune, Ch., Mostaghim, S., Steinbrecher, M.:Computational Intelligence - A Methodological Introduction, Second Edition Springer-Verlag London, 2016, ISBN 978-1-4471-7294-9
• Raza, M. S., Qamar, U.: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications, Springer Nature, 2017, ISBN 978-981-10-4964-4
• Bianchi, F. M., Maiorino, E., Kampffmeyer, M. C., Rizzi, A., Jenssen, R.:Recurrent Neural Networks for Short-Term Load Forecasting - An Overview and Comparative Analysis, SpringerBriefs in Computer Science, 2017, ISBN 978-3-319-70337-4
• Lynch, K. M., Park, F,C,: Modern Robotics. Mechanics, Planning, and Control, Cambridge U. Press, 2017, ISBN: 9781107156302

1. Introduction, soft computing and ISY
2. Expert systems
3. Intelligent information systems
4. Machine translation systems
5. Surrounding environment perception, intelligent sensor systems
6. Analysis of sensor data, environment model design
7. Planning of given tasks accomplishments
8. Control systems with neural networks
9. Fuzzy control systems
10. Neuro-fuzzy systems
11. Utilization of rough sets and genetic algorithms in ISY
12. Intelligent robotic systems
13. Navigation of mobile robots

• Two individual projects - designs of intelligent systems for solving some practical problems.

Group consultations once every two weeks.
Exam prerequisites:
The course has no credit.

Defenses of projects, oral final exam. Replacement of missed defense of the project in agreement with the subject guarantor.

The course has no credit.