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2020S, UE, 3.0h, 4.5EC

## Properties

• Semester hours: 3.0
• Credits: 4.5
• Type: UE Exercise

## Learning outcomes

After successful completion of the course, students are able to:

• Being able to work on the typical tasks of numerical mathematics in practice.
• Using numerical methods and concepts and being able to adapt them to specific questions.
• To carry out the construction of numerical algorithms or to adapt and use existing algorithms.
• Able to adapt numerical methods and procedures to given situations.
• Develop an associated solution strategy to solve numerical problems.
• To determine the influence of numerical algorithms qualitatively and quantitatively.
• Use and compare numerical algorithms in specific tasks.

## Subject of course

• Calibration of models
• Systems of linear equations
• squares problem
• Nonlinear systems of equations
• Numerical differentiation
• Ordinary differential equations
• Hybrid models
• Differential algebraic models
• Partial differential equations
• Numerical methods in data modelling

## Teaching methods

The concepts and methods of the lecture are practically examined and specific questions answered on specific tasks. The solutions are evaluated with a “score” function, which records the quality of the elaboration and compares it in the exercise group. In the face-to-face exercise itself, the solutions are presented by the students and questions from the LVA management have to be answered.

## Mode of examination

Immanent

Die Lehrveranstaltung wird gegenwärtig durch Distanzlehre abgehalten, Detailinformationen entnehmen Sie bitte dem zugehörigen TUWEL-Kurs.

## Course dates

DayTimeDateLocationDescription
Tue15:00 - 16:0003.03.2020Sem.R. DA grün 03 A - mündl. Prüfungsraum Mathematik Vorbesprechung
Tue16:00 - 19:0010.03.2020Sem.R. DA grün 03 A - mündl. Prüfungsraum Mathematik UE Mathematische Modellbildung und Simulation

## Examination modalities

Prüfungsimmanente Lehrveranstaltung

## Course registration

Begin End Deregistration end
06.03.2020 17:00 24.03.2020 09:00 24.03.2020 09:00

## Literature

No lecture notes are available.

## Previous knowledge

Basic knowledge in analysis, linear algebra and differential equations

German