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Predicting flight delays with artificial neural networks: case study of an airport

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dc.contributor.author Demir, Engin
dc.contributor.author Demir, Vahap Burhan
dc.date.accessioned 2020-02-28T07:40:59Z
dc.date.available 2020-02-28T07:40:59Z
dc.date.issued 2017
dc.identifier.citation Demir, Engin; Demir, Vahap Burhan, " tr_TR
dc.identifier.isbn 978-1-5090-6494-6
dc.identifier.uri http://hdl.handle.net/20.500.12416/2543
dc.description.abstract Air transportation has an important place among transportation systems and it is indispensable for the flights to perform their voyages in scheduled time in order to ensure the comfort of passengers and controllability of operational costs. There are several reasons for flight delays like weather conditions, excessive intensity in air traffic, accidents or closed airfields, conditions that will lead to an increase in distances between planes and operational delays in ground services. In this study, using the data collected from the sensors located in the airport and the information about the flight, the goal is develop a machine learning model to estimate departure delays of flights using artificial neural networks. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Flight Delay Estimation tr_TR
dc.subject Classification tr_TR
dc.subject Artificial Neural Networks tr_TR
dc.subject Feature Ranking tr_TR
dc.title Predicting flight delays with artificial neural networks: case study of an airport tr_TR
dc.type bookPart tr_TR
dc.relation.journal 2017 25th Signal Processing And Communications Applications Conference (SIU) tr_TR
dc.contributor.authorID 20734 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği tr_TR


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