Open Access

Vessel Crowd Movement Pattern Mining for Maritime Traffic Management

 and    | Nov 26, 2019

Cite

[1] Kleiner, F.S., Mamiya, C.J. & Tansey, R.G. (2001). Gardner’s art through the ages (11th ed.). Fort Worth, USA: Harcourt College Publishers.Search in Google Scholar

[2] Wen, R., Yan, W., Zhang, A. N., Chinh, N. Q. & Akcan, O. (2017). Spatio-temporal route mining and visualization for busy waterways. Paper presented at the 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings, 849-854. DOI:10.1109/SMC.2016.784434610.1109/SMC.2016.7844346Open DOISearch in Google Scholar

[3] Wen, R., Yan, W. & Zhang, A. N. (2017). Adaptive spatio-temporal mining for route planning and travel time estimation. Paper presented at the Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, 2018-January 3278-3284. DOI:10.1109/BigData.2017.825831110.1109/BigData.2017.8258311Open DOISearch in Google Scholar

[4] Tu, E., Zhang, G., Rachmawati, L., Rajabally, E. & Huang, G. (2018). Exploiting AIS data for intelligent maritime navigation: A comprehensive survey from data to methodology. IEEE Transactions on Intelligent Transportation Systems, 19(5), 1559-1582. DOI:10.1109/TITS.2017.272455110.1109/TITS.2017.2724551Open DOISearch in Google Scholar

[5] Yan, W., Wen, R., Zhang, A. N. & Yang, D. (2016). Vessel movement analysis and pattern discovery using density-based clustering approach. Paper presented at the Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016, 3798-3806. DOI:10.1109/BigData.2016.784105110.1109/BigData.2016.7841051Open DOISearch in Google Scholar

[6] Wen, R., Yan, W. & Zhang, A. N. (2016). Weighted clustering of spatial pattern for optimal logistics hub deployment. Paper presented at the Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016, 3792-3797. DOI:10.1109/BigData.2016.784105010.1109/BigData.2016.7841050Open DOISearch in Google Scholar

[7] Song, J., Wen, R. & Yan, W. (2016) Identification of traffic accident clusters using kulldorffs space-time scan statistics. Paper presented at the Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016, 3792-3797. DOI:10.1109/BigData.2016.784105010.1109/BigData.2016.7841050Open DOISearch in Google Scholar

[8] Lee J. G., Han J. & Whang, K.-Y. (2007). Trajectory clustering: A partitionand-group framework. Proceedings of the ACM SIGMOD International Conference on Management of Data.10.1145/1247480.1247546Search in Google Scholar

[9] Wisdom M. J., Cimon N., Johnson B., Garton E. & Thomas J. (2004). Spatial partitioning by mule deer and elk in relation to traffic. Transactions, North American Wildlife and Natural Resource Conference, 69(01).Search in Google Scholar

[10] Zhen R., Jin Y., Hu Q., Shao Z. & Nikitakos N. (2017). Maritime anomaly detection within coastal waters based on vessel trajectory clustering and nave bayes classifier. Journal of Navigation, 70(3), 648-670.10.1017/S0373463316000850Search in Google Scholar

[11] Bermingham, L. & Lee, I. (2014). Spatio-temporal sequential pattern mining for tourism sciences. Paper presented at the Procedia Computer Science, vol. 29 379-389. DOI:10.1016/j.procs.2014.05.03410.1016/j.procs.2014.05.034Open DOISearch in Google Scholar

[12] Agrafiotis, D. K. (2003). Stochastic proximity embedding. Journal of Computational Chemistry, 24(10), 1215-1221. DOI:10.1002/jcc.1023410.1002/jcc.10234Search in Google Scholar

[13] Heldens, S., Litvak, N., & Van Steen, M. (2018). Scalable detection of crowd motion patterns. IEEE Transactions on Knowledge and Data Engineering, DOI:10.1109/TKDE.2018.287907910.1109/TKDE.2018.2879079Open DOISearch in Google Scholar

[14] Peters S. & Krisp J. M. (2010). Density calculation for moving points. in GIScience 2010.Search in Google Scholar

[15] Liu, F. T., Ting, K. M. & Zhou, Z. (2008). Isolation forest. Paper presented at the Proceedings - IEEE International Conference on Data Mining, ICDM, 413-422. DOI:10.1109/ICDM.2008.1710.1109/ICDM.2008.17Open DOISearch in Google Scholar

[16] Kang, S. & Chien, W. K. (2016). A method to group reliability data by hierarchical clustering. Paper presented at the IEEE International Conference on Industrial Engineering and Engineering Management, 2016-December 345-349. DOI:10.1109/IEEM.2016.779789410.1109/IEEM.2016.7797894Open DOISearch in Google Scholar

eISSN:
2336-3037
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Business and Economics, Business Management, Industries, Transportation, Logistics, Air Traffic, Shipping