Introduction to Simulation
(in German: Introduction to Simulation - )
Module-ID: FIN-INF-120345 |
| Link: | LSF |
| Responsibility: | Graham Horton |
| Lecturer: | Graham Horton |
| Classes: |
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| Applicability in curriculum: | - M.Sc. DKE: Fundamentals of Data Science - M.Sc. DE: Grundlagen Informatik |
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Abbreviation ItS |
Credit Points 6 |
Semester Winter |
Term ab 1. |
Duration 1 Semester |
Language english |
Level Master |
Intended learning outcomes:
Students who complete the course ...
- can analyse discrete, continuous and hybrid systems using a professional simulation tool
- know how to obtain an accurate result efficiently when integrating initial value problems numerically
- can carry out input and output analysis to obtain statistically significant results for stochastic, discrete-event models
- can select an appropriate modelling paradigm for a given situation
- can perform a simulation study and interpret its results
Content:
Introduction to the fundamentals and steps in a simulation study:
- discrete-event simulation
- random variables and random number generation
- statistical data analysis
- ordinary differential equations and numerical integration
- stochastic Petri nets
- the AnyLogic simulation system
- discrete-time Markov chains
- agent-based simulation
Workload:
56 contact hours + 124 h self study
| Type of examination: | Teaching method / lecture hours per week (SWS): |
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Written exam |
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| Prerequisites according to examination regulations: | Recommended prerequisites: |
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keine |
Basic engineering mathematics |
| Media: | Literature: |
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Banks, Carson, Nelson, Nicol: Discrete-Event System Simulation |
Comments: