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...

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...

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...

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...