Title:

Modelling and Simulation

Code:MSI
Ac.Year:ukončen 2004/2005
Sem:Winter
Language of Instruction:Czech
Credits:6
Completion:credit+exam (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:3960216
 ExamsTestsExercisesLaboratoriesOther
Points:60200020
Guarantor:Rábová Zdeňka, doc. Ing., CSc. (DITS)
Lecturer:Drábek Vladimír, doc. Ing., CSc. (DCSY)
Hrubý Martin, Ing., Ph.D. (DITS)
Rábová Zdeňka, doc. Ing., CSc. (DITS)
Instructor:Drábek Vladimír, doc. Ing., CSc. (DCSY)
Florián Vladimír, Ing. (DITS)
Hrubý Martin, Ing., Ph.D. (DITS)
Slavíček Pavel, Ing. (DITS)
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
Prerequisites: 
C and C++ Programming Languages (CPP), DITS
Logic Systems (LOS), DCSY
Theoretical Computer Science 1 (TI1), DITS
 
Learning objectives:
  The goal is to introduce students to basic simulation methods and tools for modelling and simulation of continuous, discrete and combined systems.
Description:
  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.
Subject specific learning outcomes and competencies:
  Knowledge of simulation principles. The ability to create simulation model of various types. Basic knowledge of simulation system principles.
Generic learning outcomes and competencies:
  Ability to create, verify, and validate simulation models.
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 of computer exercises:
 
  • Modelling of continuous systems in object-oriented environment
  • Modelling of discrete systems
  • Petri nets in simulation
  • PNtalk system
  • Graphical support for simulation
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.
Fundamental literature:
 
  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
  • Rábová Z. a kol: Modelování a simulace, VUT Brno, 1992
Study literature:
 
  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
  • Slides available on WWW.
 

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