Modeling and simulation provide substantial support for the planning, design, and evaluation of systems as well as the evaluation of strategies for system transformation and change. Its importance continues to grow partly due to the fact that its application is not constrained by discipline boundaries. This growth is also due to the ever-widening availability of computing resources. The course will discuss basic computer science/mathematical techniques needed for the modelling and simulation of discrete and continuous dynamical systems and the interpretation of simulation results. The examples in this course will be focused on but not limited to life sciences.
Method: Lectures and Exercises
Examination: Written Exam (Maximally 100 Points). Points achieved in the exercises (Maximally 40 Points)have a positive influence on the exam grade: FinalGrade = 0.1 (PointsExercises + (1-PointsExercises/100) PointsExam)
*Objective: * – Overview on techniques used in computer simulations – Systematic insight into the spectrum of behaviors of dynamic systems – Practical skills related to the implementation and interpretation of simulation models – Simulation of processes in life science and medicine
*Prior knowledge: * Knowledge in Probability Theory, MATLAB, and Calculus will be useful but not mandatory
Literature: Hoppenstaedt and Peskin: Modeling and Simulation in Medicine and Life Sciences (2nd ed.), Springer, 2002 Francis Neelamkavil: Computer Simulation and Modelling, Wiley
Website: http://natcomp.liacs.nl/CSA
Material: The needed material will be delivered during the class.
*Remarks: * The books are not mandatory. Further literature recommendations will be announced during the class.