Zhicheng Ma
ABSTRACT
To achieve efficient and accurate identification of ship encounter behavior information in massive Automatic Identification System (AIS) data, understand and analyze the navigation process of encounter ships, and identify potential safety risk points within ports and waterways. This article takes the AIS data of the main channel area in the Qingdao sea area as the research object, uses Douglas Pucker algorithm and differential algorithm to extract the behavioral feature points of ships overtaking in the main channel, quantitatively analyzes the relationship between behavior change points and overtaking points, understands the behavioral characteristics of ships overtaking process, and provides a clearer and comprehensive understanding of the overtaking process of ships.
- Panwad Bunnak, Sotarat Thammaboosadee, and Supaporn Kiattisin. 2015. Applying Data Mining Techniques and Extended RFM Model in Customer Loyalty Measurement. https://api.semanticscholar.org/CorpusID:52829859Google Scholar
- Torkild Eriksen, Gudrun Høye, Bjørn Narheim, and Bente Jensløkken Meland. 2006. Maritime traffic monitoring using a space-based AIS receiver. Acta Astronautica 58, 10 (2006), 537–549. https://doi.org/10.1016/j.actaastro.2005.12.016Google ScholarCross Ref
- Dewan Farid and Chowdhury Rahman. 2013. Mining Complex Data Streams: Discretization, Attribute Selection and Classification. Journal of Advances in Information Technology 4 (08 2013). https://doi.org/10.4304/jait.4.3.129-135Google ScholarCross Ref
- Miao Gao and Guo-You Shi. 2020. Ship-handling behavior pattern recognition using AIS sub-trajectory clustering analysis based on the T-SNE and spectral clustering algorithms. OCEAN ENGINEERING 205 (JUN 1 2020). https://doi.org/10.1016/j.oceaneng.2020.106919Google ScholarCross Ref
- Saloni Jain. 2016. Real-Time Social Network Data Mining For Predicting The Path For A Disaster. Journal of Advances in Information Technology 7 (2016), 81–87. https://api.semanticscholar.org/CorpusID:14227682Google ScholarCross Ref
- Jun Min Mou, Cees van der Tak, and Han Ligteringen. 2010. Study on collision avoidance in busy waterways by using AIS data. OCEAN ENGINEERING 37, 5-6 (APR 2010), 483–490. https://doi.org/10.1016/j.oceaneng.2010.01.012Google ScholarCross Ref
- Chung-Yuan Nieh, Man-Chun Lee, Juan-Chen Huang, and Hsin-Chuan Kuo. 2019. RISK ASSESSMENT AND TRAFFIC BEHAVIOUR EVALUATION OF INBOUND SHIPS IN KEELUNG HARBOUR BASED ON AIS DATA. JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN 27, 4 (AUG 2019), 311–325. https://doi.org/10.6119/JMST.201908_27(4).0002Google ScholarCross Ref
- International Maritime Organization. 1972. International Regulations for Preventing Collisions at Sea (COLREGs). International Maritime Organization. https://www.imo.org/en/About/Conventions/ListOfConventions/Pages/International-Regulations-for-Preventing-Collisions-at-Sea-(COLREGs).aspxGoogle Scholar
- International Maritime Organization. 2000. Automatic Identification System (AIS). International Maritime Organization. https://www.imo.org/en/OurWork/Safety/Pages/AIS.aspxGoogle Scholar
- Yan Shi, Cheng Long, Xuexi Yang, and Min Deng. 2022. Abnormal Ship Behavior Detection Based on AIS Data. APPLIED SCIENCES-BASEL 12, 9 (MAY 2022). https://doi.org/10.3390/app12094635Google ScholarCross Ref
- Behrouz Haji Soleimani, Erico N. de Souza, Casey Hilliard, and Stan Matwin. 2015. Anomaly detection in maritime data based on geometrical analysis of trajectories. 2015 18th International Conference on Information Fusion (Fusion) (2015), 1100–1105. https://api.semanticscholar.org/CorpusID:17459493Google Scholar
- W. M. To and Peter K. C. Lee. 2018. GHG emissions from China’s international sea freight transport: a review and the future trend. INTERNATIONAL JOURNAL OF SHIPPING AND TRANSPORT LOGISTICS 10, 4 (2018), 455–467. https://doi.org/10.1504/IJSTL.2018.093483Google ScholarCross Ref
- Yuanqiao Wen, Yimeng Zhang, Liang Huang, Chunhui Zhou, Changshi Xiao, Fan Zhang, Xin Peng, Wenqiang Zhan, and Zhongyi Sui. 2019. Semantic Modelling of Ship Behavior in Harbor Based on Ontology and Dynamic Bayesian Network. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8, 3 (FEB 27 2019). https://doi.org/10.3390/ijgi8030107Google ScholarCross Ref
- Zhihao Zhang, Liang Huang, Xin Peng, Yuanqiao Wen, and Lifei Song. 2022. Loitering behavior detection and classification of vessel movements based on trajectory shape and Convolutional Neural Networks. OCEAN ENGINEERING 258 (AUG 15 2022). https://doi.org/10.1016/j.oceaneng.2022.111852Google ScholarCross Ref
- Shubin Zhong, Yuanqiao Wen, Yamin Huang, Xiaodong Cheng, and Liang Huang. 2022. Ontological Ship Behavior Modeling Based on COLREGs for Knowledge Reasoning. JOURNAL OF MARINE SCIENCE AND ENGINEERING 10, 2 (FEB 2022). https://doi.org/10.3390/jmse10020203Google ScholarCross Ref
- Yang Zhou, Winnie Daamen, Tiedo Vellinga, and Serge P. Hoogendoorn. 2020. Impacts of wind and current on ship behavior in ports and waterways: A quantitative analysis based on AIS data. OCEAN ENGINEERING 213 (OCT 1 2020). https://doi.org/10.1016/j.oceaneng.2020.107774Google ScholarCross Ref
- Yang Zhou, Winnie Daamen, Tiedo Vellinga, and Serge P. Hoogendoorn. 2023. Ship behavior during encounters in ports and waterways based on AIS data: From theoretical definitions to empirical findings. OCEAN ENGINEERING 272 (MAR 15 2023). https://doi.org/10.1016/j.oceaneng.2023.113879Google ScholarCross Ref
Index Terms
- Mining and Analysis of Ship Overtaking Behavior Based on AIS Data
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