- Degree Bachelor
- Code: CS305
- Credit hrs: 3
- Prequisites: BA203, CS243
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.
Computer Science Program
Jerry Banks, John Carson, Barry Nelson, and David Nicol, Discrete-Event System Simulation, Pearson
| content serial | Description |
|---|---|
| 1 | Introduction to Simulation |
| 2 | Steps in Simulation Study |
| 3 | Monte Carlo Simulation |
| 4 | Discrete Event Simulation |
| 5 | Statistical Models in Simulation |
| 6 | Statistical Models in Simulation (cont.) |
| 7 | 7th Week Exam |
| 8 | Random-Number Generation |
| 9 | Random-Variate Generation |
| 10 | Input Modeling |
| 11 | Output Analysis |
| 12 | 12th Week Exam |
| 13 | Markov Chain |
| 14 | Queuing Models |
| 15 | Revision |
| 16 | Final Exam |
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