Sparsity is a fundamental concept in compressive sampling of signals/images, which is
commonly measured using the l 0 norm, even though, in practice, the l 1 or the lp (0<; p<; …

In an earlier work, Sun and Bayen built a Large-Capacity Cell Transmission Model for air
traffic flow management. They formulated an integer programming problem of minimizing the …

This study proposes a mesoscopic dynamic air traffic model based on a dynamic network for
en route airspaces by characterizing the dynamics and distribution of traffic speed. Based on …

This paper presents a simulation-based evaluation of Continuous Descent Approach (CDA)
which is used as a standard terminal airspace operation at New York Metroplex airports …

An aggregate air traffic flow model based on a multicommodity network is used for traffic flow
management in the National Airspace System. The problem of minimizing the total travel …

ONE of the key objectives of optimizing air traffic in the National Airspace System (NAS) is to
achieve overall minimum delays while respecting the airspace and airport capacity …

This paper presents a dynamic network‐based approach for short‐term air traffic flow
prediction in en route airspace. A dynamic network characterizing both the topological …

The nationwide air traffic flow management problem often encounters computational
difficulty because it is generally modeled as an integer programming problem that requires …

TODAY, air traffic flow prediction is done by propagating the trajectories of the proposed
flights forward in time and using them to count the number of aircraft in a region of the …

This paper explores a new risk-hedged approach for re-routing air traffic around forecast
convective weather. In this work, flying through a more likely weather instantiation is …