We present a model for the dynamic spreading of failures in networked systems. The model combines network nodes as active, bistable elements and delayed interactions along directed links. By means of simulations, we explore the time-dependent spreading and cascade failures in different network...

Swarm intelligence is widely recognized as a powerful paradigm of self-organized optimization, with numerous examples of successful applications in distributed artificial intelligence. However, the role of physical interactions in the organization of traffic flows in ants under crowded...

The growth of world population, limitation of resources, economic problems, and environmental issues force engineers to develop increasingly efficient solutions for logistic systems. Pure optimization for efficiency, however, has often led to technical solutions that are vulnerable to variations...

The study of crowd dynamics is interesting because of the various self-organization phenomena resulting from the interactions of many pedestrians, which may improve or obstruct their flow. Besides formation of lanes of uniform walking direction and oscillations at bottlenecks at moderate...

Based on suitable video recordings of interactive pedestrian motion and improved tracking software, we apply an evolutionary optimization algorithm to determine optimal parameter specifications for the social force model. The calibrated model is then used for large-scale pedestrian simulations...

We are building a series of fast, visually accessible, cross-sectional, hence static urban models for large metropolitan areas that will enable us to rapidly test many different scenarios pertaining to both short-term and long-term urban futures. We call this framework <b>SIMULACRA</b> which is a forum...

This essay models the returns for 14 large Swedish firms' stocks with a conditional multifactor model with time-varying beta terms. The data are monthly and the sample period is June 1992 to August 1997. The beta terms are modelled as linear functions of predetermined firm attributes, which are...

This study suggests an alternative method to estimate time-varying country risk. We first apply a new multivariate stochastic volatility (SV) model to a set of emerging stock markets. To estimate the SV model, we use a Bayesian Markov chain Monte Carlo simulation procedure. By applying the...

This study looks at the time-varying nature of systematic risk in the Greater China equity markets. The Shanghai and Shenzhen markets both have a low average systematic risk when measured against the world market. The short outbursts in systematic risk for these two markets seem to be directly...

In this essay we model the returns for 14 large Swedish firms' stocks with a conditional multifactor model with time-varying beta terms. The data are monthly and the sample period is June 1992 to August 1997. The beta terms are modelled as linear functions of predetermined firm attributes, which...