A novel method for identifying key focus ships in a complex network based on ship collision risks

As the navigation conditions of ships in regulated waters become increasingly complex, how to construct an intuitive maritime collision risk network and accurately identify sailing ships with higher collision risks in the waters has become a hot issue. This study constructs a complex network called SCRCN based on ship collision risks, and identifies key focus ships on it. In this method, ship positions are represented as nodes in the SCRCN, and the edges and weights of the SCRCN are determined by calculating ship collision risks based on mutual movement trends, dynamic collision boundaries, distance margin, and time margin. 7 indicators are selected: ship length, individual ship comprehensive collision risk, degree, weighted clustering coefficient, weighted betweenness centrality, weighted closeness centrality, and Katz centrality. The entropy weight method is used to combine them to measure the key focus degree of the ships, and the top of the ships are ranked according to the key focus degree as the key focus ships. The method's rationality and effectiveness are validated through experimental analysis using AIS data from part of the Ningbo-Zhoushan Port water and robustness testing. The study has practical significance for promoting the intelligent development of VTS supervision and ensuring maritime navigation safety.