UIN1203 Softcomputing and its applications

Faculty of Philosophy and Science in Opava
Winter 2023
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
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
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
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
The course is also listed under the following terms Winter 2012, Winter 2013, Winter 2014, Winter 2015, Winter 2016, Winter 2017, Winter 2018, Winter 2019, Winter 2020, Winter 2021, Winter 2022.
  • Enrolment Statistics (recent)
  • Permalink: https://is.slu.cz/course/fpf/winter2023/UIN1203