Flight delays hurt airlines, airports, and passengers. Their prediction is crucial during the
decision-making process for all players of commercial aviation. Moreover, the development …

Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …

This study analyzes high-dimensional data from Beijing International Airport and presents a
practical flight delay prediction model. Following a multifactor approach, a novel deep belief …

To better understand the mechanism of flight delay propagation at the system-level, we built
a delay causality network (DCN) based on the Granger causality test. Through topological …

Flight delay prediction has recently gained growing popularity due to the significant role it
plays in efficient airline and airport operation. Most of the previous prediction works consider …

Data science and analytics are attracting more and more attention from researchers and
practitioners in recent years. Due to the rapid development of advanced technologies …

To probe deeply into the underlying mechanism of flight delay propagation, we construct the
delay propagation networks among airports via refined nonlinear Granger causality, which is …

We developed an airline network delay propagation model using a Bayesian Network in a
delay-tree framework, accounting for multiple connecting sources of an airline including …

We build a delay propagation network based on Bayesian Network approach to study the
complex phenomenon of delay propagation within a large network consisting of the 100 …

It has been widely recognized that delay propagation is a widespread phenomenon in air
transport systems. Regional air transport systems are vulnerable to severe systemic delay …