With the increase in the number of ships and the intensifying maritime traffic, maritime accidents such as ship collisions and grounding occur frequently, posing serious threats to people's lives and property. Therefore, timely detection and correction of abnormal ship behaviors are of great significance for improving navigation safety. The Automatic Identification System (AIS) can provide real-time information on ships' positions, speeds, headings, and more, offering a rich data resource for data mining. Through the analysis of these data, it is possible to deeply explore the navigation patterns and characteristics of abnormal behaviors of ships. This paper applies data mining technology to the detection of abnormal ship behaviors, which not only improves the accuracy and efficiency of detection but also provides maritime regulatory authorities with richer decision-making support.
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