MATH220 Mathematical Modelling

The course introduces the student to different forms of mathematical models, how they can be used and interpreted.

1. Ordinary Differential Equations (ODE) models: The derivation of ODEs as models of phenomena such as population dynamics, chemical reactions, etc. Numerical solution of ODEs. Partial differential equations as limits of systems of ODEs.
2. Graph/NetworkModels: How graphs/networks can be used to model relations and interactions such as the internet, transportation networks, electrical circuits, etc.
3. Stochastic models: How uncertainty can be introduced in models via random variables. Examples of stochastic models covered are Markov Chains, Poisson point processes and Kalman filters.

Knowledge

After completing the course, the student will be familiar with different forms of mathematical models, their derivation and uses.

Skills The student will be able to apply the methods from the course to analyze models and solve practical problems where these methods are relevant.

General competence

The student will be able to use computer tools to do implement and compute with the models.