Course detail

Methods and Algorithms for System Simulation and Optimization

FSI-9MASAcad. year: 2023/2024

The course deals with the following topics: Classification of elements and systems. Numerical simulation methods. Modelling by means of formal systems, finite automata and Petri nets. Continuous, discrete, mixed and object-oriented simulation systems. Artificial intelligence methods in simulation and optimization. Using neural networks and evolutionary algorithms for classification and prediction.

Language of instruction

Czech

Mode of study

Not applicable.

Guarantor

prof. RNDr. Ing. Jiří Šťastný, CSc.

Department

Institute of Automation and Computer Science (ÚAI)

Entry knowledge

Fundamentals of mathematics, including differential and integral calculus of functions in one and more variables and solution of system differential equations. Fundamentals of physics, mechanics, electrical engineering and automatic control, knowledge of basic programming techniques.

Rules for evaluation and completion of the course

Exam has a written and an oral part and tests students’ knowledge of the subject-matter covered in the course.
Attendance at seminars is checked by means of projects.

Aims

The aim of the course is to make students familiar with the methods and selected software supporting the computer simulation.
Students will be able to use software methods and applications for simulation.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Fishwick, P.: Simulation Model Design and Execution, Building Digital Worlds, Prentice-Hall, 1995
Goldberg, D. E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addisson-Wesley Professional,1989
Norgaard, M.: Neural Networks for Modelling and Control of Dynamic Systems, Springer, 2000
Zeigler, B., Praehofer, H., Kim, T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000

Recommended reading

Mandic, Danilo P.: Recurrent neural networks for prediction, learning algorithms, architectures and stability, Wiley, Chichester 2001
O´Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary automatic programming in an arbitrary language. Kluwer Academic publishers, 2003
Ross, S.: Simulation, 3rd edition, Academic Press, 2002

Classification of course in study plans

  • Programme D-KPI-P Doctoral 1 year of study, summer semester, recommended course
  • Programme D-KPI-K Doctoral 1 year of study, summer semester, recommended course

Type of course unit

 

Lecture

20 hod., optionally

Teacher / Lecturer

prof. RNDr. Ing. Jiří Šťastný, CSc.

Syllabus

1. Introduction to computer simulation and optimization methods.
2. Classification of elements and systems.
3. Numerical simulation methods.
4. Modelling by means of formal systems.
5. Modelling by means of finite automata and Petri nets.
6. Continuous, discrete, mixed and object-oriented simulation systems.
7. Artificial intelligence methods in modelling and simulation.
8. Artificial intelligence methods in optimization and identification.
9. Using neural networks for classification and prediction.
10. Using evolutionary algorithms for classification and prediction.