All Tracks

Complex systems consist of a large number of strongly interacting elements, often denoted as agents. Complex networks are a specific representation of such systems, where agents are

We follow the short-ranged Syrian refugees’ migration to Lebanon as documented by the UNHCR. We propose a model inspired by the Debye–Hückel theory and show that it properly predicts the refugees’ mobility while the gravity model fails.

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others.

This paper applies non linear methods to analyze and predict the weekly Gas and Oil prices. The aim of the analysis is to quantitatively show if the corresponding time series are deterministic chaotic and if they are predictable. The research employs Grassberger and Procaccia methodology into the time series analysis in order to estimate the correlation and minimum embedding dimensions of the corresponding strange attractor. In order to achieve out of sample one week ahead prediction, a local weighted least squares over all neighbors’ projections k-steps into the future has been applied.

Humans are a primate species with a unique social organization; we live in groups that are characterized by predominant kin and non-kin pair bonds. Although the nature of the relationship between individual members of the society is crucial to understand social network dynamics, this information is typically not available in “big data” datasets.

Reactive explorers to unravel network topology.
Ihusan Adam1,2, Timoteo Carletti3, Duccio Fanelli4, Giacomo Innocenti5
(1) Dipartimento di Fisica e Astronomia, Universita di Firenze, INFN, Firenze, Italy
(2) Dipartimento di Ingeneria, Universita di Firenze, INFN, Firenze, Italy
(3) Namur Institute for Complex Systems, naXys, University of Namur, Namur, Belgium\
(4) Dipartimento di Fisica e Astronomia, Universita di Firenze, INFN and CSDC, Firenze, Italy
(5) Dipartimento di Ingeneria, Universita di Firenze, INFN and CSDC, Firenze, Italy