Research on ship trajectory extraction based on multiattribute DBSCAN optimisation algorithm

• Autorzy: Xu Xiaofeng , Cui Deqaing , Li Yun , Xiao Yingjie

Identyfikatory

DOI

10.2478/pomr-2021-0013

• Języki publikacji: EN

Abstrakty

EN

With the vigorous development of maritime traffic, the importance of maritime navigation safety is increasing day by day. Ship trajectory extraction and analysis play an important role in ensuring navigation safety. At present, the DBSCAN (density-based spatial clustering of applications with noise) algorithm is the most common method in the research of ship trajectory extraction, but it has shortcomings such as missing ship trajectories in the process of trajectory division. The improved multi-attribute DBSCAN algorithm avoids trajectory division and greatly reduces the probability of missing sub-trajectories. By introducing the position, speed and heading of the ship track point, dividing the complex water area and vectorising the ship track, the function of guaranteeing the track integrity can be achieved and the ship clustering effect can be better realised. The result shows that the cluster fitting effect reaches up to 99.83%, which proves that the multi-attribute DBSCAN algorithm and cluster analysis algorithm have higher reliability and provide better theoretical guidance for the analysis of ship abnormal behaviour.

Słowa kluczowe

EN

clustering algorithm; abnormal route; DBSCAN; feature trajectory extraction; fitting analysis

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2021
• Tom: nr 1
• Strony: 136--148
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Xu Xiaofeng

• Shanghai Maritime University, Haigang streat, 201306 ShangHai, China

autor

Cui Deqaing

• Shanghai Maritime University, Haigang streat, 201306 ShangHai, China

autor

Li Yun

• Shanghai Maritime University, Haigang streat, 201306 ShangHai, China

autor

Xiao Yingjie

• Shanghai Maritime University, Haigang streat, 201306 ShangHai, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).