Self-learning adaptive algorithm for maritime traffic abnormal movement detection based on virtual pheromone method

Julius Venskus, Mindaugas Kurmis, Arunas Andziulis, Zydrunas Lukosius, Miroslav Voznak, Denisas Bykovas. Self-learning adaptive algorithm for maritime traffic abnormal movement detection based on virtual pheromone method. In Floriano De Rango, Franco Davoli, José-Luis Marzo, Joel Rodrigues, Malamati D. Louta, Imadeldin Mahgoub, José Saldaña, Saurabh Mittal, José Luis Risco-Martín, Deniz Cetinkaya, editors, Proceedings of the International Symposium on Performance Evaluation of Computer and Telecommunication Systems, Chicago, IL, USA, July 26-29, 2015. ACM, 2015. [doi]

@inproceedings{VenskusKALVB15,
  title = {Self-learning adaptive algorithm for maritime traffic abnormal movement detection based on virtual pheromone method},
  author = {Julius Venskus and Mindaugas Kurmis and Arunas Andziulis and Zydrunas Lukosius and Miroslav Voznak and Denisas Bykovas},
  year = {2015},
  url = {http://dl.acm.org/citation.cfm?id=2875000},
  researchr = {https://researchr.org/publication/VenskusKALVB15},
  cites = {0},
  citedby = {0},
  booktitle = {Proceedings of the International Symposium on Performance Evaluation of Computer and Telecommunication Systems, Chicago, IL, USA, July 26-29, 2015},
  editor = {Floriano De Rango and Franco Davoli and José-Luis Marzo and Joel Rodrigues and Malamati D. Louta and Imadeldin Mahgoub and José Saldaña and Saurabh Mittal and José Luis Risco-Martín and Deniz Cetinkaya},
  publisher = {ACM},
  isbn = {978-1-5108-1060-0},
}