Ground-Air Traffic Congestion Propagation Model Based on Hierarchical Control Interdependent Network
Why this work is in the frame
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Bibliographic record
Abstract
A multilayer network approach to model and analyze air traffic networks is proposed. These networks are viewed as complex systems with interactions between airports, airspaces, procedures, and air traffic flows (ATFs). A topology-based airport-airspace network and a flight trajectory network are developed to represent critical physical and operational characteristics. A multilayer traffic flow network and an interrelated traffic congestion propagation network are also formulated to represent the ATF connection and congestion propagation dynamics, respectively. Furthermore, a set of analytical metrics, including those of airport surface (AS), terminal controlled airspace (TCA), and area-controlled airspace (ACA), is introduced and applied to a case study in central and south-eastern China. The empirical results show the existence of a fundamental diagram of the airport, terminal, and intersections of air routes. Moreover, the dynamics and underlying mechanisms of congestion propagation through the AS-TCA-ACA network are revealed and interpreted using the classical susceptible-infectious-removed model in a hierarchical network. Finally, a high propagation probability among adjacent terminals and a high recovery probability are identified at the network system level. This study provides analytical tools for comprehending the complex interactions among air traffic systems and identifies future developments and automation of layered coupled air traffic management systems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it