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 underpinnings, 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 queuing theory. Finally, the course describes and illustrates modeling of some applications using simulation software.

Program

Computer Science bachelor`s degree Program

Objectives

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

Textbook

JERRY BANKS, JOHN CARSON II , DISCRETE-EVENT SYSTEM SIMULATION , PEARSON

Course Content

content serial Description
1Introduction to Simulation
2Steps in Simulation Study
3Monte Carlo Simulation
4Discrete Event Simulation
5Statistical Models in Simulation
6Random-Number Generation
7Random-Variate Generation
8Input Modeling
9Output Analysis part 1
10Output Analysis part 2
11Markov Chain part 1
12Markov Chain part 2
13Queuing Models part 1
14Queuing Models part 2
15Revision

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.
Courses
  • Degree Bachelor
  • Code: CCS3003
  • Credit hrs: 3
  • Prequisites: EBA2203, CCS2303
Download.pdf
Apply Now

Start your application

Start The your journey to your new career.
SUBMIT IT NOW