Simulation Tools and Techniques
|Language of Instruction:||Czech, English|
|Guarantor:||Češka Milan, prof. RNDr., CSc. (DITS)|
|Lecturer:||Peringer Petr, Dr. Ing. (DITS)|
|Instructor:||Hrubý Martin, Ing., Ph.D. (DITS)|
|Faculty:||Faculty of Information Technology BUT|
|Department:||Department of Intelligent Systems FIT BUT|
| || ||Students will be introduced to design and implementation principles of simulation systems. Further, the methods and techniques for modelling and simulation of various types of models will be presented.|
| || ||Theory of modelling and simulation, DEVS (Discrete Event System Specification) formalism. Simulation systems, their design and implementation. Algorithms used for simulation control, parallel and distributed simulation. Continuous, discrete, and combined simulation: model description methods, simulation tools, numerical methods. Special types of models; corresponding methods, techniques, and tools. Modelling of systems described by partial differential equations. Multimodels. Knowledge-based simulation. Model validation and verification. Simulation experiment control. Simulation results analysis and visualization. Simulation system case study.|
|Knowledge and skills required for the course:|
| || ||Basic knowledge of modelling, simulation, algorithms, and numerical mathematics.|
|Subject specific learning outcomes and competencies:|
| || ||The basics of modelling and simulation theory. Understanding the principles of simulation system implementation. Knowledge of advanced simulation methods and techniques.|
|Generic learning outcomes and competencies:|
| || ||creation of simulation tools, models, and practical use of simulation techniques|
|Syllabus of lectures:|
- Introduction. Types of problems, which can be solved using simulation methods. Theory of modelling and simulation, DEVS formalism.
- Simulation systems: classification, principles of design and implementation. Simulation control algorithms. Parallel and distributed simulation.
- Continuous simulation: numerical methods, stiff systems, algebraic loops.
- Discrete simulation: implementation of events and processes. Queueing systems.
- Combined simulation: state events.
- Modelling of systems described by partial differential equations. Basics of sensitivity analysis.
- Digital systems simulation models and tools.
- Traffic systems simulation. Cellular automata.
- Models of uncertainty, using fuzzy logic in simulation. Knowledge-based simulation.
- Multimodels. Model optimization methods. Qualitative simulation.
- Simulation experiment control, simulation results analysis. Theoretical foundations of model validation and verification.
- Modern visualization methods. User interfaces of simulation systems. Simulation and virtual reality.
- Simulation system implementation case study. Examples of simulation models.
|Syllabus - others, projects and individual work of students:|
- Individual solution of specified simulation problem, or extending of given simulation system to allow the use of new modelling methods.
- Fishwick, P.: Simulation Model Design and Execution, Prentice Hall, 1995, ISBN 0-13-098609-7
- Law, A., Kelton, D.: Simulation Modelling and Analysis, McGraw-Hill, 2000, ISBN 0-07-100803-9
- Zeigler, B., Praehofer, H., Kim, T.: Theory of Modelling and
Simulation, second edition, Academic Press, 2000, ISBN 0-12-778455-1
- Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1
- Rábová Z. a kol.: Modelování a simulace, VUT Brno, 1992, ISBN 80-214-0480-9
- Slides available online at WWW page.