Flight diversion detection

A machine-learning based approach for the automated detection of flight diversions based on public flight data.

For further information, please refer to:

• the journal article: Claudio Di Ciccio, Han van der Aa, Cristina Cabanillas, Jan Mendling, Johannes Prescher: Detecting flight trajectory anomalies and predicting diversions in freight transportation. Decision Support Systems 88: 1-17 (2016). DOI: 10.1016/j.dss.2016.05.004;
• the slides and extended abstract presented at the 7th International Workshop on Enterprise Modeling and Information Systems Architectures (EMISA 2016);
• the explanatory video and the blog post for the WU Researcher of the Month award (August 2018).