Number of documents
16
Xavier Olive, PhD, is a research scientist passionate about aviation, maps and data. His research interests include Data Science, Machine Learning and Decision Science applied to aviation, with a particular focus on optimisation, anomaly and pattern detection. Applications range from air traffic management, operations, predictive maintenance, safety analyses and risk assessment.
He is currently a Research Fellow with ONERA, The French Aerospace Lab. You may find more details on https://www.xoolive.org.
Journal articles6 documents
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Luis Basora, Paloma Bry, Xavier Olive, Floris Freeman. Aircraft Fleet Health Monitoring with Anomaly Detection Techniques. Aerospace, MDPI, 2021, 8 (4), pp.103. ⟨10.3390/aerospace8040103⟩. ⟨hal-03196104⟩
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Sana Ikli, Catherine Mancel, Marcel Mongeau, Xavier Olive, Emmanuel Rachelson. The aircraft runway scheduling problem: A survey. Computers and Operations Research, Elsevier, 2021, Volume 132, August 2021, pp.105336. ⟨10.1016/j.cor.2021.105336⟩. ⟨hal-03204701⟩
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Xavier Olive, Luis Basora. Detection and identification of significant events in historical aircraft trajectory data. Transportation research. Part C, Emerging technologies, Elsevier, 2020, 119, pp.102737. ⟨10.1016/j.trc.2020.102737⟩. ⟨hal-02972531⟩
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Xavier Olive. Traffic, a toolbox for processing and analysing air traffic data. Journal of Open Source Software, Open Journals, 2019, 4 (39), pp.1518, 1-3. ⟨10.21105/joss.01518⟩. ⟨hal-02294354⟩
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Luis Basora, Xavier Olive, Thomas Dubot. Recent Advances in Anomaly Detection Methods Applied to Aviation. Aerospace, MDPI, 2019, 6 (117), pp.1-27. ⟨10.3390/aerospace6110117⟩. ⟨hal-02470453⟩
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Xavier Olive, Jérôme Morio. Trajectory clustering of air traffic flows around airports. Aerospace Science and Technology, Elsevier, 2018, 84, pp.776-781. ⟨10.1016/j.ast.2018.11.031⟩. ⟨hal-02350789⟩
Conference papers10 documents
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Michael Schultz, Xavier Olive, Judith Rosenow, Hartmut Fricke, Sameer Alam. Analysis of airport ground operations based on ADS-B data. 2020 International Conference on Artificial Intelligence and Data Analytics for Air Transportation (AIDA-AT), Feb 2020, Singapour, Singapore. pp.1-9, ⟨10.1109/AIDA-AT48540.2020.9049212⟩. ⟨hal-03182721⟩
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Sana Ikli, Catherine Mancel, Marcel Mongeau, Xavier Olive, Emmanuel Rachelson. Coupling Mathematical Optimization and Machine Learning for the Aircraft Landing Problem. ICRAT 2020, 9th International Conference for Research in Air Transportation, Jun 2020, Tampa, United States. ⟨hal-02873423⟩
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Xavier Olive, Luis Basora, Benoit Viry, Richard Alligier. Deep Trajectory Clustering with Autoencoders. ICRAT 2020, 9th International Conference for Research in Air Transportation, Sep 2020, Tampa, United States. ⟨hal-02916241⟩
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Sana Ikli, Catherine Mancel, Marcel Mongeau, Xavier Olive, Emmanuel Rachelson. Approche de programmation mixte en nombres entiers pour le séquencement d’avions en atterrissage - cas statique. ROADEF 2019, 20ème congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision, Feb 2019, Le Havre, France. ⟨hal-02050005⟩
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Xavier Olive, Luis Basora. Identifying Anomalies in past en-route Trajectories with Clustering and Anomaly Detection Methods. ATM Seminar 2019, Jun 2019, VIENNE, Austria. ⟨hal-02345597⟩
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Xavier Olive, Luis Basora. A Python Toolbox for Processing Air Traffic Data: A Use Case with Trajectory Clustering. 7th OpenSky Workshop 2019, Nov 2019, Zurich, Switzerland. pp.73-60, ⟨10.29007/sf1f⟩. ⟨hal-02650267⟩
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Michael Schultz, Judith Rosenow, Xavier Olive. A-CDM Lite: Situation Awareness and Decision- making for Small Airports based on ADS-B Data. 9th SESAR Innovation Days: Inspiring Long-Term Research in the Field of Air Traffic Management, SIDs 2019, Dec 2019, Athènes, Greece. ⟨hal-02623883⟩
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Sana Ikli, Catherine Mancel, Marcel Mongeau, Xavier Olive, Emmanuel Rachelson. An Optimistic Planning Approach for the Aircraft Landing Problem. EIWAC 2019:, 6th ENRI International Workshop on ATM/CNS, ENRI, Oct 2019, Tokyo, Japan. pp 173-188, ⟨10.1007/978-981-33-4669-7_10⟩. ⟨hal-02382692⟩
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Xavier Olive, Pierre Bieber. Quantitative Assessments of Runway Excursion Precursors using Mode S data. ICRAT - International Conference for Research in Air Transportation, Jun 2018, Castelldefels, Spain. ⟨hal-02078299⟩
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Xavier Olive, Jeremy Grignard, Thomas Dubot, Julie Saint-Lot. Detecting Controllers' Actions in Past Mode S Data by Autoencoder-Based Anomaly Detection. SID 2018, 8th SESAR Innovation Days, Dec 2018, Salzburg, Austria. ⟨hal-02338690⟩