|本期目录/Table of Contents|

[1]赵吟秋,索永峰,鲜波.基于AIS数据的船舶会遇挖掘与分析[J].集美大学学报(自然科学版),2022,27(4):326-332.
 ZHAO Yinqiu,SUO Yongfeng,XIAN Bo.Mining and Analysis of Ship Encounters Based on AIS Big Data[J].Journal of Jimei University,2022,27(4):326-332.
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基于AIS数据的船舶会遇挖掘与分析(PDF)
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《集美大学学报(自然科学版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第27卷
期数:
2022年第4期
页码:
326-332
栏目:
航海技术与物流工程
出版日期:
2022-07-28

文章信息/Info

Title:
Mining and Analysis of Ship Encounters Based on AIS Big Data
作者:
赵吟秋索永峰鲜波
(1.集美大学航海学院,福建 厦门361021;2.集美大学航海技术研究所,福建 厦门 361021)
Author(s):
ZHAO YinqiuSUO YongfengXIAN Bo
(1.Navigation College,Jimei University,Xiamen 361012,China;2.The Navigation Technology Institude,Jimei University,Xiamen 361012,China)
关键词:
船舶自动识别系统DBSCAN聚类船舶会遇时空特性分析
Keywords:
AISDBSCAN clusteringship encountersanalysis of temporal and spatial characteristics
分类号:
-
DOI:
-
文献标志码:
A
摘要:
为实现在AIS海量数据中快速高效地识别会遇船舶信息,对会遇船舶航行过程实施监控和分析,识别研究水域内存在的海上交通安全风险点。以台湾海峡部分区域内的AIS数据作为研究对象,运用改进的DBSCAN聚类算法,结合船舶会遇特征参数计算,挖掘两船会遇与多船会遇信息,根据船舶方位和航向差划分船舶交叉、对遇和追越三种会遇局面,并通过定量化方式多维度描述不同类型的船舶会遇过程。结果表明:分析轨迹数据的时空特性可以再现船舶会遇场景,能更清晰全面地展现船舶的会遇过程。
Abstract:
In order to realize the rapid and efficient identification of encountering ships in the massive data of AIS, the research monitors the navigation process of encountering ships by using an improved DBSCAN clustering algorithm,which is well used in rapid extraction of maritime traffic safety risks in the research water area. Through the combination of ship encounters feature parameter calculations and using AIS data within the Taiwan Strait area as the research object, dual ship encounters and multi-ship encounters are mined effectively. Then the encounter situations are divided into three types, ie, cross encounters, head-on encounters and overtaking encounters, based on the ships’ bearing and course differences. Finally, the encounter processes of different types of ships are described in multiple dimensions, the encounter scenes of the ship are reproduced through a quantitative? method and time-space characteristics analysis. The results show the analysis of time-space chatacteristics can reproduce ships encounter situations and illstrustrate the encounter process more clearly and comprehensively.

参考文献/References:

相似文献/References:

[1]张银昊,潘家财,赵梦鸽.阈值引导采样法的船舶轨迹简化算法[J].集美大学学报(自然科学版),2021,26(5):425.
 ZHANG Yinhao,PAN Jiacai,ZHAO Mengge.A Ship Trajectory Simplified Algorithm Based on Threshold Guiding Sampling Method[J].Journal of Jimei University,2021,26(4):425.

备注/Memo

备注/Memo:
更新日期/Last Update: 2022-09-10