Open Access
Volume 39, Number 1, February 2021
Page(s) 119 - 125
Published online 09 April 2021
  1. Mao Jiali, Jin Cheqing, Zhang Zhigang, et al. Anomaly detection for trajectory big data: advancements and framework[J]. Journal of Software, 2017, 28(1):17–34 [Article] (in Chinese) [Google Scholar]
  2. Anagnostopoulos C, Hadjiefthymiades S. Intelligent trajectory classification for improved movement prediction[J]. IEEE Trans on Systems Man & Cybernetics Systems, 2014, 44(10):1301–1314 [Article] [Google Scholar]
  3. Yuan G, Sun P, Zhao J, et al. A Review of moving object trajectory clustering algorithms[J]. Artificial Intelligence Review, 2017, 47(1):123–144 [Article] [Google Scholar]
  4. Qiao S, Han N, Zhu W, et al. TraPlan: an effective three-in-one trajectory-prediction model in transportation networks[J]. IEEE Trans on Intelligent Transportation Systems, 2015, 16(3):1188–1198 [Article] [Google Scholar]
  5. Yuan G, Zhao J, Xia S, et al. Multi-granularity periodic activity discovery for moving objects[J]. International Journal of Geographical Information Science, 2017, 31(3):435–462 [Article] [Google Scholar]
  6. Fernandez A V, Pallotta G, Vespe M. Maritime traffic networks: from historical positioning data to unsupervised maritime traffic monitoring[J]. IEEE Trans on Intelligent Transportation Systems, 2017: 722–732 [Article] [Google Scholar]
  7. Tu E, Zhang G, Rachmawati L, et al. Exploiting AIS data for intelligent maritime navigation: a comprehensive survey[J]. IEEE Trans on Intelligent Transportation Systems, 2016, 19(5):1–24 [Google Scholar]
  8. Wu Jianhua, Wu Chen, Liu Wen, et al. Automatic detection and restoration algorithm for trajectory anomalies of ship AIS[J]. Navigation of China, 2017, 40(1):8–12 [Article] (in Chinese) [Google Scholar]
  9. Soleimani B H, De souza E N, Hilliard C, et al. Anomaly detection in maritime data based on geometrical analysis of trajectories[C]//2015 18th International Conference on Information Fusion, Washington DC USA, 2015: 1100–1105 [Google Scholar]
  10. Li Jia, Chu Xiumin, Liu Xinglong, et al. An approach for restoring the lost trajectories of vessels in inland waterways[J]. Journal of Harbin Engineering University, 2019, 40(1):67–73 [Article] (in Chinese) [Google Scholar]
  11. Zhang D, Li J, Wu Q, et al. Enhance the AIS data availability by screening and interpolation[C]//2017 4th International Conference on Transportation Information and Safety, Banff, Canada, 2017: 981–986 [Google Scholar]
  12. Rong H, Teixeira A P, Soares G G. Data mining approach to shipping route characterization and anomaly detection based on ais Data[J]. Ocean Engineering, 2020, 198(106936):1–12 [Article] [Google Scholar]
  13. ITU-R M.1371-5[EB/OL]. (2014-02-01)[2020-05-01]. [Article] [Google Scholar]
  14. Historical AIS Data Services[EB/OL]. (2018-12-10)[2020-05-01]. [Article], 2018-12-10 [Google Scholar]

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