ArticleScientific reports2023
Evaluation of the impact of Covid-19 on air traffic volume in Turkish airspace using artificial neural networks and time series.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Optimized capacitance sensor configuration with enhanced sensitivity for annular two-phase flow measurement.Scientific reports · 2025Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In early 2020, the aviation sector was one of the business lines adversely affected by the Covid 19 outbreak that affected the whole world. As a result, some countries imposed travel restrictions. Following these restrictions, air traffic density has decreased significantly worldwide. Since air traffic density directly affects almost all operations in air transportation, analyzing these data is very essential. For this purpose, SARIMA models, one of the linear time series models, and multilayer perceptron model (MLP), one of the artificial neural network methods suitable for nonlinear modeling, were applied to the air traffic data regarding Turkish airspace between 2010 and 2019, and the actual air traffic density was compared with the forecasts obtained from these analyses. It is considered that the results of this study are essential for organizations conducting aviation operations to take into consideration while doing future planning.
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