{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T05:26:54Z","timestamp":1750138014550,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030623647"},{"type":"electronic","value":"9783030623654"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-62365-4_14","type":"book-chapter","created":{"date-parts":[[2020,10,29]],"date-time":"2020-10-29T06:02:51Z","timestamp":1603951371000},"page":"148-155","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports"],"prefix":"10.1007","author":[{"given":"N\u00e9stor","family":"Jim\u00e9nez-Campfens","sequence":"first","affiliation":[]},{"given":"Adri\u00e1n","family":"Colomer","sequence":"additional","affiliation":[]},{"given":"Javier","family":"N\u00fa\u00f1ez","sequence":"additional","affiliation":[]},{"given":"Juan M.","family":"Mogoll\u00f3n","sequence":"additional","affiliation":[]},{"given":"Antonio L.","family":"Rodr\u00edguez","sequence":"additional","affiliation":[]},{"given":"Valery","family":"Naranjo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,27]]},"reference":[{"key":"14_CR1","unstructured":"Pilot and technical outlook: Seattle. Boeing Commercial Airplanes, WA (2015)"},{"key":"14_CR2","unstructured":"Wolter, C.A., Gore, B.F.: NASA\/TM-2015-218480: A validated task analysis of the Single Pilot Operations concept, no. January 2015 (2015)"},{"issue":"5","key":"14_CR3","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1108\/00022660710780650","volume":"79","author":"D Harris","year":"2007","unstructured":"Harris, D.: A human-centred design agenda for the development of single crew operated commercial aircraft. Aircr. Eng. Aerosp. Technol. 79(5), 518\u2013526 (2007)","journal-title":"Aircr. Eng. Aerosp. Technol."},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Bailey, R.E., Kramer, L.J., Kennedy, K.D., Stephens, C.L., Etherington, T.J.: An assessment of reduced crew and single pilot operations in commercial transport aircraft operations. In: AIAA\/IEEE Digital Avionics System Conference - Proceedings, vol. 2017-September, no. February 2018 (2017)","DOI":"10.1109\/DASC.2017.8101988"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Lachter, J., Brandt, S.L., Battiste, V., Ligda, S.V., Matessa, M., Johnson, W.W.: Toward single pilot operations: developing a ground station. In: Proceedings of International Conference on Human-Computer Interactive Aerospace, August (2014)","DOI":"10.1145\/2669592.2669685"},{"key":"14_CR6","unstructured":"Comerford, D., Brandt, S.L., Mogford, R.: NASA\/CP - 2013\u2013216513 NASA\u2019s Single -Pilot Operations Technical Interchange Meeting: Proceedings and Findings, April, p. 89 (2013)"},{"issue":"3","key":"14_CR7","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1023\/A:1026507809196","volume":"13","author":"N Durand","year":"2000","unstructured":"Durand, N., Alliot, J.M., M\u00e9dioni, F.: Neural nets trained by genetic algorithms for collision avoidance. Appl. Intell. 13(3), 205\u2013213 (2000)","journal-title":"Appl. Intell."},{"key":"14_CR8","doi-asserted-by":"crossref","unstructured":"Choi, S., Kim, Y.J., Briceno, S., Mavris, D.: Prediction of weather-induced airline delays based on machine learning algorithms. In: 2016 IEEE\/AIAA 35th Digital Avionics Systems Conference (DASC), pp. 1\u20136. IEEE, September 2016","DOI":"10.1109\/DASC.2016.7777956"},{"key":"14_CR9","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/TVT.2019.2954094","volume":"69","author":"G Gui","year":"2019","unstructured":"Gui, G., Liu, F., Sun, J., Yang, J., Zhou, Z., Zhao, D.: Flight delay prediction based on aviation big data and machine learning. IEEE Trans. Veh. Technol. 69, 140\u2013150 (2019)","journal-title":"IEEE Trans. Veh. Technol."},{"key":"14_CR10","unstructured":"Liu, Y., Hansen, M.: Predicting aircraft trajectories: a deep generative convolutional recurrent neural networks approach. arXiv preprint arXiv:1812.11670 (2018)"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Shi, Z., Xu, M., Pan, Q., Yan, B., Zhang, H.: LSTM-based flight trajectory prediction. In: 2018 IEEE International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138, July 2018","DOI":"10.1109\/IJCNN.2018.8489734"},{"key":"14_CR12","doi-asserted-by":"crossref","unstructured":"Bosson, C.D., Nikoleris, T.: Supervised learning applied to air traffic trajectory classification. In: 2018 AIAA Information Systems-AIAA Infotech@ Aerospace, p. 1637 (2018)","DOI":"10.2514\/6.2018-1637"},{"key":"14_CR13","unstructured":"FlightRadar24 website. https:\/\/www.flightradar24.com\/"},{"key":"14_CR14","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 (2015)"},{"issue":"1","key":"14_CR15","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"14_CR16","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"14_CR17","unstructured":"Chollet, F., et al.: Keras (2015). https:\/\/keras.io"}],"container-title":["Lecture Notes in Computer Science","Intelligent Data Engineering and Automated Learning \u2013 IDEAL 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-62365-4_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:04:40Z","timestamp":1710266680000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-62365-4_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030623647","9783030623654"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-62365-4_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"27 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDEAL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Data Engineering and Automated Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guimaraes","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 November 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ideal2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/islab.di.uminho.pt\/ideal2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"134","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"93","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"69% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.8","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}