Faculty of Information Technology, BUT

Course details

Modelling and Simulation

MSI Acad. year 2006/2007 Winter semester 6 credits

Course is not open in this year
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Introduction to modelling and simulation concepts. System analysis and classification. Abstract and simulation models. Continuous, discrete, and combined models. Heterogeneous models. Using Petri nets and finite automata in simulation. Pseudorandom number generation and testing. Queuing systems. Monte Carlo method. Continuous simulation. Simulation experiment control. Visualization and analysis of simulation results.

Guarantor

Peringer Petr, Dr. Ing. (DITS FIT BUT)

Language of instruction

Czech

Completion

Credit+Examination (written)

Time span

39 hrs lectures, 10 hrs pc labs, 16 hrs projects

Assessment points

50 exam, 20 half-term test, 10 exercises, 20 projects

Department

Subject specific learning outcomes and competences

Knowledge of simulation principles. The ability to create simulation model of various types. Basic knowledge of simulation system principles.

Generic learning outcomes and competences

Ability to create, verify, and validate simulation models.

Learning objectives

The goal is to introduce students to basic simulation methods and tools for modelling and simulation of continuous, discrete and combined systems.

Prerequisites

Prerequisite kwnowledge and skills

Programming in the C/C++ language. Basic knowledge of numerical mathematics.

Study literature

  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995, ISBN 0-13-098609-7 
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991, ISBN 0-07-100803-9
  • Slides available on WWW.

Fundamental literature

  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995, ISBN 0-13-098609-7 
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991, ISBN 0-07-100803-9
  • Rábová Z. a kol: Modelování a simulace, VUT Brno, 1992, ISBN 80-214-0480-9

Syllabus of lectures

  • Introduction to modelling and simulation. System analysis, clasification of systems. System theory basics, its relation to simulation.
  • Model classification: conceptual, abstract, and simulation models. Heterogeneous models. Methodology of model building.
  • Simulation systems and languages, means for model and experiment description. Principles of simulation system design.
  • Parallel process modelling. Using Petri nets and finite automata in simulation.
  • Models o queuing systems. Discrete simulation models. Model time, simulation experiment control.
  • Continuous systems modelling. Overview of numerical methods used for continuous simulation.
  • Combined simulation. The role of simulation in digital systems design.
  • Special model classes, models of heterogeneous systems.
  • Checking model validity, verification of models. Analysis of simulation results.
  • Simulation results visualization. Interactive simulation, virtual reality.
  • Design and control of simulation experiments. Model optimization.
  • Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo method.
  • Overview of commonly used simulation systems.

Syllabus - others, projects and individual work of students

  • Individual selection of suitable problem, its analysis, simulation model creation, experimenting with model, and analysis of results.

Controlled instruction

Mid-term exam (incl. test if it is declared), laboratory practice supported by a project and final exam are the monitored, and points earning, education.
Mid-term exam and laboratory practice (supported by the project) are without alternative. Final exam has two additional alternatives.

Exam prerequisites

  • Individual project has to receive at least 5 points.
  • The project and the mid-term exam  receive at least 15 points.
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