Szarmach, MartaCzarnowski, Ireneusz2023-09-222023-09-222023Szarmach M., Czarnowski I., Identification of Damaged AIS Data Based on Clustering and Multi-Label Classification. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 167-172, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.26.978-83-66741-92-8http://hdl.handle.net/11652/4802https://doi.org/10.34658/9788366741928.26Automatic Identification System (AIS) is a telecommunication system that allows ships to communicate with each other by sending information regarding their trajectory: location, speed, course and so on. Due to some technical issues, some parts of the transmitted data might be damaged or incomplete. In this paper, we propose a machine learning based approach for detecting AIS data that requires reconstruction. The general idea of the proposed approach, utilizing clustering and mutli-label classification algorithms, and its performance are discussed.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionAIS data analysisanomaly detectionmultilabel classificationautomatic identification systemanaliza danych AISwykrywanie anomaliiklasyfikacja wieloetykietowasystem automatycznej identyfikacjiRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.26