654-0929/01 – Modelling of industrial processes (MPP)
| Gurantor department | Department of Industrial Systems Management | Credits | 10 |
| Subject guarantor | doc. Ing. Milan Heger, CSc. | Subject version guarantor | doc. Ing. Milan Heger, CSc. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2022/2023 | Year of cancellation | |
| Intended for the faculties | FMT, HGF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Student will be able to formulate the basic methods of simulation models realization on the digital computer, to create mathematical models of selected industrial processes with aim of classic simulation programs and with artificial neural networks exploitation. Student will get an overview of the basic principles of mathematic-physical modelling, similarity and modelling and of classic and artificial intelligence methods necessary for model realization.
Teaching methods
Individual consultations
Project work
Summary
The course deals with physical and mathematical modelling of industrial processes. Students are acquainted with analytical and experimental methods of identification of the mathematical description of the dynamic system and with methods necessary for implementation of the model on a digital computer. Students are introduced to artificial intelligence (fuzzy models, expert models, models of neural networks, genetic algorithms), attention is paid mainly to the models of neural networks and their application to the selected industrial processes.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Ústní zkouška
E-learning
Other requirements
Elaboratin of seminar work on a given topic.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Introduction to systems modelling.
2. Mathematical description of dynamic systems.
3. Physical modelling.
4. Mathematical modelling, analogy.
5. Analytical and experimental methods of system identification.
6. Simulation of systems.
7. Simulation program SIMULINK, creation of simulation models of selected
industrial processes.
8. Unconventional modelling, artificial intelligence.
9. Neural networks, neuron models, learning and generalisation of neural
networks, learning algorithms.
10. Creation of neural networks models of selected industrial processes in
software tools NEUREX, Statistika Neural Networks and MATLAB Neural Network
Toolbox.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.