Identifying and modelling correlation between airport weather conditions and additional time in airport arrival sequencing and metering area

被引：0

作者：

Bagamanova M. ^{[1
]}

González J.J.R. ^{[1
]}

Eroles M.A.P. ^{[1
]}

García J.M.C. ^{[2
]}

Rodríguez-Sanz Á. ^{[3
]}

机构：

[1] Universitat Autònoma de Barcelona, Carrer de Emprius 2, Sabadell

[2] CRIDA A.I.E. (Reference Center for Research, Development and Innovation in ATM), Edificio Allende, Avenida de Aragón 402, Madrid

[3] Universidad Politécnica de Madrid, Plaza Cardenal Cisneros 3, Madrid

来源：

International Journal of Simulation and Process Modelling | 2019年 / 14卷 / 03期

关键词：

Airport; ASMA time; Bayesian networks; Coloured Petri net; CPN; Decision support tool; Holding; Inbound traffic; TMA model; Weather impact;

D O I：

10.1504/IJSPM.2019.101003

中图分类号：

学科分类号：

摘要：

Different uncertainties during operational activities of modern airports can significantly delay some processes and cause chain-effect performance drop on the overall air traffic management (ATM) system. The decision-making process to mitigate the propagation of perturbations through the different airport processes can be improved with the support of a causal model, built with a use of data mining and machine learning techniques. This paper introduces a new approach for modelling causal relationships between various ATM performance indicators, which can be used to predict, by means of simulation techniques, the evolution of airport operations scenarios. The analysis of reachable airport states is a relevant approach to design mitigation mechanisms on those perturbations which drive the system to poor KPIs. Copyright © 2019 Inderscience Enterprises Ltd.

引用

页码：213 / 222

页数：9