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Modelling and Simulation

Module IN2010

This Module is offered by TUM Department of Informatics.

This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.

Module version of SS 2012 (current)

There are historic module descriptions of this module. A module description is valid until replaced by a newer one.

available module versions
SS 2012WS 2011/2

Basic Information

IN2010 is a semester module in English language at Bachelor’s level and Master’s level which is offered in summer semester.

This Module is included in the following catalogues within the study programs in physics.

  • Catalogue of non-physics elective courses
Total workloadContact hoursCredits (ECTS)
240 h 90 h 8 CP

Content, Learning Outcome and Preconditions

Content

- Introduction to mathematical modelling (notions and notations, fields of application, derivation of models, analysis of models, classification of models, scales and hierarchy)
- Discrete modelling and simulation (decision models: games, strategies, elections; scheduling problems; discrete event simulation: data and job traffic; neural networks)
- Continuous modelling and simulation (population dynamics: models and their numerical treatment; control: deterministic and fuzzy logic approaches; traffic flow: modelling via continuous quantities; heat conduction: models and their numerical treatment)
- Modelling in software design (optional; basic concepts, description techniques, methodology)

Learning Outcome

The participants are able to develop and to assess formal (mathematical or infomatical) model concepts for a verbally described problem. They can select and apply successfully strategies for simulation, i.e., the computer-aided solution of these models. They know exemplary important model classes and can develop own solution procedures for simple scenarios.

Preconditions

MA0901 Linear Algebra for Informatics, MA0902 Analysis for Informatics, IN0019 Numerical Programming

Courses, Learning and Teaching Methods and Literature

Courses and Schedule

TypeSWSTitleLecturer(s)Dates
VO 4 Modelling and Simulation (IN2010) Reiz, S. Sarbu, P.
Responsible/Coordination: Bungartz, H.
Wed, 10:00–12:00, Interims I 101
Tue, 16:00–18:00, Interims I 101
and singular or moved dates
UE 2 Modelling and Simulation, Exercise Session (IN2010) Reiz, S. Sarbu, P.
Responsible/Coordination: Bungartz, H.
dates in groups

Learning and Teaching Methods

This module comprises lectures and accompanying tutorials. The contents of the lectures will be taught by talks and presentations.
Students will be encouraged to study literature and to get involved with the topics in depth. In the tutorials, concrete problems will be solved - partially in teamwork - and selected examples will be discussed.

Media

Slides, whiteboard, exercise sheets

Literature

- Bungartz, Zimmer, Buchholz, Pflüger: Modellbildung und Simulation - eine anwendungsorientierte Einführung, Springer, 2009
- Fowkes, Mahoney: Einführung in die mathematische Modellierung, Spektrum,1996
- Gander, Hrebicek: Solving Problems in Scientific Computing Using Maple and MATLAB, Springer, 1997
- Bossel: Modellbildung und Simulation, Vieweg, 1994
- Banks et al.: Discrete Event System Simulation, Prentice Hall, 1996
- Golub, Ortega: Scientific Computing: An Introduction with Parallel Computing, Academic Press, 1993
- Nauck, Klawonn, Kruse: Neuronale Netze und Fuzzy-Systeme, Vieweg, 1994

Module Exam

Description of exams and course work

Type of Assessment: exam

The exam takes the form of a 120 minutes written test. In the exam students should prove to be able to identify a given problem and find solutions within limited time. The examination will completely cover the content of the lectures. The answers will require own formulations. In addition, questions requiring short calculations may be posed. Exam questions check the ability to develop and to assess formal (mathematical or informatical) model concepts for a verbally described problem. The assignments test whether the participants are able to select and apply successfully strategies for simulation. Exam tasks evaluate the students' knowledge on important model classes and corresponding solution procedures for simple scenarios.

Exam Repetition

The exam may be repeated at the end of the semester.

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