Stochastic simulation - understanding chance on the computer

The term "simulation" covers all approaches in which the parameters of complex systems (e.g. train traffic) are determined by observing a computer model. "Stochastic simulation" takes particular account of the influence of random factors such as demand, weather and technical faults. This training course uses a number of real examples to show how reliable statements about the real system can be made from the simulated observations. It also explains how "random" values can be generated on the computer by simple means and used, for example, to calculate integrals.

Program

09.30 - 09.45Welcome Prof. Dr. W. Klotz
09.45 - 10.45Stochastic simulation: applications and methods (Prof. Dr. Th. Hanschke)
10.45 - 11.15Coffee break
11.15 - 12.00Generation of random numbers and Monte Carlo methods (Prof. Dr. M. Kolonko)
12.00 - 13.15Lunch break
13.15 - 14.30Simulation exercises part I
14.30 - 15.00Coffee break
15.00 - 16.00Simulation exercises part II
16.00 - 16.30Discussion and closing remarks