Course details

Modelling and Simulation

MSD Acad. year 2005/2006 Winter semester

Current academic year

Simulation systems, their classification. Design and implementation of simulation systems. Continuous, discrete, and combined system simulation. Special types of models. Parallel and distributed simulation. Knowledge-based simulation, model optimization. Simulation results analysis and visualization. Simulation for virtual reality.

Guarantor

Rábová Zdeňka, doc. Ing., CSc.

Language of instruction

Czech, English

Completion

Examination

Time span

  • 39 hrs lectures
  • 9 hrs pc labs

Department

Department of Intelligent Systems (UITS)

Subject specific learning outcomes and competences

The basics of modelling and simulation theory. Understanding the principles of simulation system implementation. Knowledge of advanced simulation techniques.

Create, verify, and validate simulation models.

Learning objectives

Students will be introduced to design and implementation principles of simulation systems. Further, the techniques for modelling and simulation of various types of models will be presented.

Prerequisite knowledge and skills

There are no prerequisites

Study literature

  • Rábová Z. a kol: Modelování a simulace, VUT Brno, 2002
  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
  • Didier H. Besset: Object-Oriented Implementation of Numerical Methods: An Introduction with Java & Smalltalk, Morgan Kaufmann, 2000
  • Zeigler B., Kim T., Praehofer H.: Theory of Modeling and Simulation. Academic Press Inc.,U.S.; 2nd Edition edition. 2000. ISBN: 0127784551
  • Sarjoughian H., Cellier F.: Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies. Springer-Verlag New York Inc. 2001. ISBN: 0387950656

Fundamental literature

  • Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995
  • Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991
  • Ross S.: Simulation, Academic Press, 2002
  • Zeigler B., Kim T., Praehofer H.: Theory of Modeling and Simulation. Academic Press Inc.,U.S.; 2nd Edition edition. 2000. ISBN: 0127784551
  • Sarjoughian H., Cellier F.: Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies. Springer-Verlag New York Inc. 2001. ISBN: 0387950656

Syllabus of lectures

  • Introduction. Types of problems, which can be solved using simulation methods. Dynamical systems theory.
  • Simulation systems and their classification. Principles of simulation system design and implementation. Using general programming languages for simulation.
  • Algorithms for controll of simulation.
  • Continuous simulation: numerical methods, spatial models.
  • Discrete simulation: events, processes, quasiparallel execution.
  • Combined simulation: state events.
  • Advanced and special simulation methods. Basics of sensitivity analysis.
  • Digital system models. Qualitative simulation. Models of uncertainity, using fuzzy logic in simulation. Knowledge-based simulation. Model optimization.
  • Parallel and distributed simulation.
  • Modern visualization methods. User interfaces of simulation systems and models.
  • Simulation for virtual reality.
  • Teoretic foundations of model validation and verification. Simulation results analysis.
  • Application of artifical inteligence principles to system modelling and simulation. Examples of heterogeneous models.

Progress assessment

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Controlled instruction

There are no checked study.

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