Air traffic flow management regulations: big data analytics

Sánchez Vázquez, Ignacio

Publication:
Air traffic flow management regulations: big data analytics

dc.contributor.advisor	García-Heras Carretero, Javier
dc.contributor.author	Sánchez Vázquez, Ignacio
dc.contributor.departamento	UC3M. Departamento de Bioingeniería e Ingeniería Aeroespacial	es
dc.coverage.spatial	east=15.2551187; north=54.5259614; name=Europa
dc.date.accessioned	2020-01-27T14:36:37Z
dc.date.available	2020-01-27T14:36:37Z
dc.date.issued	2018-09
dc.date.submitted	2018-09-09
dc.description.abstract	Air traffic in Europe is constantly increasing. Due to this, Air Traffic Management is getting more complex and all stakeholders get affected by that. Among these, air traffic controllers are the ones that suffer the biggest impact in terms of overload of work. Every day, a set of regulations occurs in the regions controlled by these operators, which provokes delays on ground and rerouting in mid-air. All of these variations directly affect the entire ATM network and translates into big expenses for passengers and airlines. With this project, the aim is to predict these daily contingencies by using big data analysis models, so that costs associated are reduced. Most of the information needed to run the analysis has been very complicated to extract, process and correlate because the data sources are not open to researchers. Therefore, the number of instances available for the prediction is very low (only 18 months of data). Nevertheless, while working with this limitation, a Naive Bayes classifier has been chosen as the analytical algorithm. In terms of results, the work done does not reveal a high predictive capability due to the amount of data acquired and the simplicity of the temporal variables. This suggests that, in future researches, it could be convenient to intake broader historical data (more years). Moreover, more complex predictive models could be implemented if variables coming from the weather or the number of flights are used.	es
dc.description.degree	Ingeniería Aeroespacial (Plan 2010)	es
dc.identifier.uri	https://hdl.handle.net/10016/29552
dc.language.iso	eng	es
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España	*
dc.rights.accessRights	open access	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/	*
dc.subject.eciencia	Aeronáutica	es
dc.subject.other	Air traffic control (ATC)	es
dc.subject.other	Big data	es
dc.subject.other	Air Traffic Control Centers	es
dc.subject.other	Python (Programming language)	es
dc.subject.other	Data Mining	es
dc.title	Air traffic flow management regulations: big data analytics	es
dc.type	bachelor thesis	*
dspace.entity.type	Publication