2020
DOI: 10.3390/app10186165
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Characterization and Prediction of Air Transport Delays in China

Abstract: Air transport delays are a major source of direct and opportunity costs in modern societies, being this problem is especially important in the case of China. In spite of this, our knowledge on delay generation is mostly based on intuition, and the scientific community has hitherto devoted little attention to this topic. We here present the first data-driven systemic study of air transport delays in China, of their evolution and causes, based on 11 million flights between 2016 and 2018. A significant fraction o… Show more

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Cited by 17 publications
(8 citation statements)
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“…In recent years, average departure delay has also attracted much attention. Research on departure delay optimization [34,35] and prediction [36,37] has achieved prominent results. For temporal local risk factors, we adopt average departure delay due to its significant position in air traffic risk assessment.…”
Section: Risk Coupling Modelmentioning
confidence: 99%
“…In recent years, average departure delay has also attracted much attention. Research on departure delay optimization [34,35] and prediction [36,37] has achieved prominent results. For temporal local risk factors, we adopt average departure delay due to its significant position in air traffic risk assessment.…”
Section: Risk Coupling Modelmentioning
confidence: 99%
“…Among the weather factors affecting the safety and efficiency of air traffic, TSTM is the most unfavorable weather phenomenon (Zanin et al, 2020). During the lifecycle of a thunderstorm cell (cumulus, mature, and dissipating), the three stages are dominated by strong ascending motions, coexisting updrafts, and downdrafts, as well as downdrafts, respectively.…”
Section: Introductionmentioning
confidence: 99%
“…In search of the indicators that address network resiliency, ATFM delay (among various types of delays in ATM) is receiving more attention, since the comparative American and European reports categorized almost 80 percent of delays as the ATFM delay [11]. Recent studies [12][13][14] tend to address delay prediction with machine learning (ML) methods, which benefit from data availability in aviation compared to other means of transportation.…”
Section: Introductionmentioning
confidence: 99%