| Abstract |
Being able to make predictions on the behavior of crowds allows for the exploration of the effectiveness of certain measures to control crowds. Taking effective measures might be crucial to avoid severe consequences in case the crowd goes out of control. Recently, a number of simulation models have been developed for crowd behavior and the descriptive capabilities of these models have been shown. In this presentation I will discuss the predictive capabilities of these complex models based upon real data. Hereby, techniques from the domain of computational intelligence are used to find appropriate parameter settings for the model. Furthermore, a comparison is shown with an alternative approach, namely to utilize neural networks for the same purpose. |