Course detail
Intelligent Systems
FIT-ISDAcad. year: 2023/2024
Tolerance of imprecision and uncertainty as main attribute of ISY. Intelligent systems based on combinations of several theories - neural networks, fuzzy sets, rough sets and genetic algorithms: expert systems, intelligent information systems, machine translation systems, intelligent sensor systems, intelligent control systems, intelligent robotic systems.
Topics for the SDE (state doctoral exam)
- Fuzzy expert systems
- Knowledge engineering using soft-computing
- Intelligent sensor systems
- Neural networks in intelligent systems
- Fuzzy control systems
- Neuro-fuzzy control systems
- Rough sets in intelligent systems
- Genetic algorithms in intelligent systems
- Inteligent robots
- Navigation of mobile robots
Language of instruction
Mode of study
Guarantor
Department
Entry knowledge
Rules for evaluation and completion of the course
Defenses of projects, oral final exam. Replacement of missed defense of the project in agreement with the subject guarantor.
Aims
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.
Study aids
Prerequisites and corequisites
Basic literature
Recommended reading
Bramer, M.: Principles of Data Mining, Second edition, Springer-Verlag London 2013, ISBN 978-1-4471-4883-8
Iba, H., Noman, N.: New Frontier in Evolutionary Algorithms, Imperial College Press, 2012, ISBN-13 978-1-84816-681-3
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
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
Classification of course in study plans
- Programme DIT Doctoral 0 year of study, summer semester, compulsory-optional
- Programme DIT Doctoral 0 year of study, summer semester, compulsory-optional
- Programme DIT-EN Doctoral 0 year of study, summer semester, compulsory-optional
- Programme DIT-EN Doctoral 0 year of study, summer semester, compulsory-optional
- Programme CSE-PHD-4 Doctoral
branch DVI4 , 0 year of study, summer semester, elective
- Programme CSE-PHD-4 Doctoral
branch DVI4 , 0 year of study, summer semester, elective
- Programme CSE-PHD-4 Doctoral
branch DVI4 , 0 year of study, summer semester, elective
- Programme CSE-PHD-4 Doctoral
branch DVI4 , 0 year of study, summer semester, elective
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- Introduction, soft computing and ISY
- Expert systems
- Intelligent information systems
- Machine translation systems
- Surrounding environment perception, intelligent sensor systems
- Analysis of sensor data, environment model design
- Planning of given tasks accomplishments
- Control systems with neural networks
- Fuzzy control systems
- Neuro-fuzzy systems
- Utilization of rough sets and genetic algorithms in ISY
- Intelligent robotic systems
- Navigation of mobile robots
Guided consultation in combined form of studies
Teacher / Lecturer
Project
Teacher / Lecturer
Syllabus
- Two individual projects - designs of intelligent systems for solving some practical problems.