Weight distributions of American domestic passenger air transportation networks

Abstract

The scale-free features widely concerned by previous weighted network models seemed to not be the best choice to describe the link weight distributions of passenger air transportation networks. In this paper, by introducing an exponent α to the weight evolution rule of the earliest weighted model, and considering the spatial constraints of two-dimensional distances on linking probability, we have conducted rigorous analyses leading to the exponentially truncated power-law distribution for weights: P ( w ) = A ⋅ w − α ⋅ e − B w 1 − α , where A and B are parameters, α < 1. The theoretical expression is consistent with the empirical results of the American domestic passenger flight records from 1995 to 2020. The model would be applicable to different air transportation systems and to problems in other fields.

Centrality anomalies for the domestic air transportation networks in the USA: an empirical benchmark

“…As another note, recently, we introduced a new model by adding an exponent to Eq. ( 3 ) and generated the exponentially truncated power-law weight distributions consistent with the American domestic air transportation networks [ 49 ]. The statistical results of eigenvector centrality and betweenness anomalies of this model are also calculated, which are not affected by the exponent .…”

Hyper-network models for civil aviation systems

“…Assuming the nodes are added to the system with a constant speed, the time intervals between two successive additions are identical, that is, P (t) = 1/(m 0 + t) [10]. Then eq.…”