Prediction of air traffic complexity through a dynamic complexity indicator and machine learning models
Francisco Pérez Moreno, Fernando Ibáñez Rodríguez, Víctor Fernando Gómez Comendador, Raquel Delgado-Aguilera Jurado, María Zamarreño Suárez, Rosa María Arnaldo Valdés
| Year of publication: |
2024
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|---|---|
| Authors: | Pérez Moreno, Francisco ; Ibáñez Rodríguez, Fernando ; Gómez Comendador, Víctor Fernando ; Delgado-Aguilera Jurado, Raquel ; Zamarreño Suárez, María ; Arnaldo Valdés, Rosa María |
| Published in: |
Journal of air transport management : a new international journal of research, policy and practice. - Amsterdam [u.a.] : Elsevier Science, ZDB-ID 2027741-6. - Vol. 119.2024, Art.-No. 102632, p. 1-18
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| Subject: | Complexity | Machine learning | Random forest | Air traffic flows | Air traffic management | Künstliche Intelligenz | Artificial intelligence | Luftverkehr | Air transport | Prognoseverfahren | Forecasting model | Luftverkehrssicherheit | Aviation safety |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.jairtraman.2024.102632 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015083680