This paper presents a new class of models for predicting air traffic delays. The proposed models consider both temporal and spatial (that is, network) delay states as explanatory variables, and use Random Forest algorithms to predict departure delays 2-24 hours in the future. In addition to local delay variables that describe the arrival or departure delay states of the most influential airport...

in this paper, a bidirectional associative memory (bam) neural network, which consists of two neurons in the x-layer and three neurons in the y-layer, with two time delays will be studied. we conclude that under some assumptions, hopf bifurcation occurs when the sum of two delays passes through a critical value. a numerical example is presented to support our theoretical results.

A memory control for T-S fuzzy discrete-time systems with sto- chastic input delay is proposed in this paper. Dierent from the common assumptions on the time delay in the existing literatures, it is assumed in this paper that the delays vary randomly and satisfy some probabilistic dis- tribution. A new state space model of the discrete-time T-S fuzzy system is derived by introducing some stocha...

This paper aims to investigate the robustness of exponential synchronization in complex dynamic networks (CDNs) with time-varying delays and random disturbances. Via Gronwall–Bellman lemma partial inequality methods, by calculating transcendental equations, limits maximum disturbance size CDNs are estimated. means that perturbed system achieves if strength is within our estimation range. The th...

Abstract Many urban rail systems operate near capacity given the rapid increase in passenger demand, and unplanned disruptions are unavoidable. From a perspective, duration of trip delays is major concern, may be longer than train delays. Several studies have focused on predicting delays, but research disruption impacts trips limited that not observed directly. This paper proposes probabilistic...