System Modeling and Simulation

  • College of Computing & Information Technology |
  • English

Description

The course gives the theoretic aspects of simulation, followed by its probabilistic and statistical un-derpinnings, including random number generation. It addresses simulation-related theory of input analysis, and output analysis. It also provides a background about Markov chain processes and queu-ing theory. Finally, the course describes and illustrates modeling of some applications using simula-tion software.

Program

Computer Science Program

Objectives

  • 1. Understand the basic principles of the field of Modeling and Simulation.
    2. Apply standard statistical techniques in analyzing input data for a simulation experiment.
    3. Use Markov chains theory for modeling of queuing systems.
    4. Plan for and design a simulation experiment for some problems
    5. Evaluate performance of queuing systems.

Textbook

Jerry Banks, John Carson, Barry Nelson, and David Nicol, Discrete-Event System Simulation, Pearson

Course Content

content serial Description

Markets and Career

  • Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
  • Electrical power feeding for civil and military marine and aviation utilities.
  • Electrical works in construction engineering.

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