Method for hierarchical clustering analysis of warship and ship trajectories based on buffer similarity measurement

Abstract

The invention provides a method for hierarchical clustering analysis of warship and ship trajectories based on buffer similarity measurement. Similarity measurement on channel trajectory clustering based on buffer analysis is given, and weaknesses of large calculated amount and non-steady clustering effect in a conventional method are overcome; at the same time, situations of a huge amount of warship and ship trajectories and existence of noises are considered, a hierarchical clustering method which is efficient and likely to reduce noises is adopted, and a threshold selection process is revealed. Due to the application of the method, a massive amount of warship and ship trajectories on regional sea can be subjected to hierarchical clustering, so that the distribution of main ship routes is mastered and a foundation for finding activity routines of warships and ships, mentoring marine traffic, improving channel environments, guaranteeing channel safety and the like is laid.

Description

technical field [0001] The invention relates to a clustering analysis method for linear trajectories, in particular to a hierarchical clustering analysis method for ship trajectories based on buffer similarity measurement. Background technique [0002] A channel is a ribbon-shaped area formed by the trajectories of ships between ports. The control of the actual waterway is beneficial to the maritime supervision department to discover the rules of ship activities, monitor the sea traffic, improve the environment of the waterway, and ensure the safety of the waterway. Most of the existing ship trajectories come from the automatic report of the ship automatic identification system (AIS). However, the complicated and massive ship trajectory data in the AIS database, coupled with a large amount of ship trajectory noise, makes it difficult to highlight the characteristics of the distribution of major sea lanes in the region. . Therefore, how to reasonably cluster the existing sh...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is: to overcome the above-mentioned defects of the prior art, to propose a hierarchical clustering analysis method for ship trajectories based on buffer similarity measurement, to generate vector ship trajectory space clustering results, and to avoid existing The clustering method is not sensitive to anomaly detection and has the shortcomings of large noise. A similarity measure based on buffer analysis for the track trajectory is given, which overcomes the large amount of calculation of the traditional method and may be due to improper selection of certain measurement attributes. Weaknesses that cause results to be less than expected

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