Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Modelling Dependence of Arrival Sequencing and Metering Area Transit Time on Airport Meteorological Conditions
Year:2017
Research Areas
  • Aircraft operation,
  • Air traffic management,
  • Air transport,
  • Airport
Information
Abstract
Airports are considered complex system in which the coexistence of different actors competing and collaborating for the same resources under operational time uncertainties can cause a poor performance on the overall ATM (Air Traffic Management) system. In order to facilitate the process of decision making to mitigate the propagation of perturbations through the different airport processes a causal model relying on machine learning, using data mining algorithms has been implemented to predict feasible states. This paper introduces a new approach for modelling causal relationships, which can be used for further analysing of feasible scenarios by means of simulation techniques. The state space analysis of reachable airport states is a relevant approach to validate the causal model using a huge amount of historical data for predictive purposes.
International
Si
Congress
European Modeling and Simulation Symposium. Multidisciplinary Modeling and Simulation Multiconference (I3M 2017)
960
Place
Reviewers
Si
ISBN/ISSN
978-88-97999-85-0
Start Date
18/09/2017
End Date
20/09/2017
From page
288
To page
295
Proceedings of the European Modeling and Simulation Symposium, 2017
Participants
  • Autor: Alvaro Rodriguez Sanz (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Navegación Aérea
  • Departamento: Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos
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