arXiv (OAI Expanded)
open access
Probabilistic Multi-Agent Aircraft Landing Time Prediction
Accurate and reliable aircraft landing time prediction is essential for effective resource allocation in air traffic management. However, the inherent uncertainty of aircraft trajectories and traffic flows poses significant challenges to both prediction accuracy and trustworthiness. Therefore, predi
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Probabilistic Multi-Agent Aircraft Landing Time Prediction#819272
- Uncertainty-Aware Conflict Detection Against Operator-Conditioned Weather Hazards#1000066
- Toward a Decision-Assurance Layer for AI-Assisted Flight Planning in Air Traffic Management#1071332
- Unlocking air traffic flow prediction through microscopic aircraft-state modeling#665750
- Unlocking air traffic flow prediction through microscopic aircraft-state modeling#664250
Record · ID 809280
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive