FPF:UIN1203 Softcomputing and its applicat - Course Information
UIN1203 Softcomputing and its applications
Faculty of Philosophy and Science in OpavaWinter 2020
- Extent and Intensity
- 0/2/0. 2 credit(s). Type of Completion: z (credit).
- Teacher(s)
- Ing. Jiří Blahuta, Ph.D. (seminar tutor)
doc. Ing. Petr Čermák, Ph.D. (seminar tutor)
RNDr. Jiří Martinů, Ph.D. (seminar tutor) - Guaranteed by
- doc. Ing. Petr Čermák, Ph.D.
Institute of Computer Science – Faculty of Philosophy and Science in Opava - Timetable of Seminar Groups
- UIN1203/A: each even Friday 12:15–15:30 B3a, J. Blahuta
- Prerequisites (in Czech)
- TYP_STUDIA(N)
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Computer Science and Technology (programme FPF, N1801 Inf)
- Course objectives
- This course is focused on modern methods of problem solving by means of vagueness and its tolerance primarily in practical application area. Softcomputing methods have a lot of application for example in robotics.
- Syllabus
- Students will be introduced to basics of the best known softcomputing methods and their practical using chiefly in robotics. Inseparable part of the course is also description of using softcomputing methods to design of advanced forms of management and control systems and also to optimalisation problems.
1. Introduction to softcomputing, basic terms
2. Artificial neural networks
3. Fuzzy systems
4. Fuzzy rule-based system for management and control
5. Genetic algorithms
6. Bayesian Networks
7. The application of the softcomputing in robotics
8. The application of the softcomputing to controlling in 2-D space
9. The application of the softcomputing to controlling in 3-D space (UAV)
10. Optimalisation problems
11. Basics of Chaos Theory
- Students will be introduced to basics of the best known softcomputing methods and their practical using chiefly in robotics. Inseparable part of the course is also description of using softcomputing methods to design of advanced forms of management and control systems and also to optimalisation problems.
- Literature
- required literature
- HYNEK, J. Genetické algoritmy a genetické programování. Praha, 2008. ISBN 978-80-247-6057-5. info
- VYSOKÝ, P. Fuzzy řízení. Praha, 1996. ISBN 80-01-01429-8. info
- ŠÍMA, J., NERUDA, R. Teoretické otázky neuronových sítí. 1996. URL info
- recommended literature
- CVITANOVIC, P., ARTUSO, R., MAINIERI, R., TANNER, G., VATTA, G. Chaos: Classical and Quantum. 2015. URL info
- Shima, T., Rasmussen, S. UAV Cooperative Decision and Control, Challenges and Practical Approaches, Researchers and Collaborators Control. SIAM, 2009. ISBN 978-0-898716-64-1. info
- HECKERMAN D. A Tutorial on Learning With Bayesian Networks. Redmont, 1995. URL info
- Teaching methods
- Interactive lecture
Lecture with a video analysis - Assessment methods
- Credit
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course can also be completed outside the examination period. - Teacher's information
- * 75% attendance in exercises, active participation
* Seminar work, implementation of selected softcomputing methods (40 points)
* 60 points from written test
- Enrolment Statistics (Winter 2020, recent)
- Permalink: https://is.slu.cz/course/fpf/winter2020/UIN1203