摘要
船舶交通管理(VTS)对覆盖区域内的船舶密集区域进行有效识别,并对区域内的船舶实施远程预警,可以提升通航效率,减少海上险情事故。通过改进K-means聚类算法建立海上船舶密集区域识别模型,并设计VTS船舶密集区预警系统,结合AIS数据实验模拟,该算法对船舶密集区域的识别是有效且可行的。
The vessel traffic service(VTS)is capable of effectively identifying dense ship traffic areas within waters covered by VTS and conducting remote pre-warning for ships within the areas,which helps to improve navigation efficiency and reduce the occurrence of maritime dangerous situations and accidents.In this paper,the identification model of dense ship traffic areas is established and the pre-warning system is designed through improving the K-means algorithm.In light of the experimental simulation of AIS data,the algorithm is applied to VTS,which is effective and feasible for the identification of dense traffic waters.
作者
王代楠
陈琼
Wang Dai-nan;Chen Qiong
出处
《中国海事》
2022年第1期53-56,共4页
China Maritime Safety
关键词
K-MEANS
差分进化算法
VTS
海事
VTS远程预警
K-means
differential evolution(DE)
vessel traffic service(VTS)
maritime
VTS remote pre-warning
