基于云分段最优熵算法的航行异常轨迹识别研究  

Research on navigation anomaly trajectory recognition based on cloud segmented optimal entropy algorithm

作　　者：陈小海[1] 甘杜芬[1] CHEN Xiao-hai;GAN DU-fen(The Computer Engineering College,Guilin University of Electronic Technology,Beihai 536000,China)

机构地区：[1]桂林电子科技大学计算机工程学院,广西北海536000

出　　处：《舰船科学技术》2022年第7期150-153,共4页Ship Science and Technology

摘　　要：海洋运输业的迅速发展对大型航运公司的船舶管理水平提出了更高要求,随着船舶数量的迅速增加,针对船舶航行异常轨迹的识别和监控技术成为了研究热点。本文对如何提高船舶航行异常轨迹的识别效果进行了研究,引入一种基于AIS和雷达的航行轨迹识别系统,基于云分段最优熵算法,实现了船舶航行异常轨迹数据的快速识别和剔除,有助于提高海上航运公司对船舶管理水平,及早发现船舶的异常航行状态并进行航线调整,防止船舶事故的发生。The rapid development of marine transportation industry puts forward higher requirements for the ship management level of large shipping companies. With the rapid increase of the number of ships, the identification and monitoring technology of ship navigation abnormal trajectory has become a research hotspot. This paper studies how to improve the recognition effect of ship navigation abnormal trajectory, introduces a navigation trajectory recognition system based on AIS and radar, and realizes the rapid recognition and elimination of ship navigation abnormal trajectory data based on cloud segmented optimal entropy algorithm, which is helpful to improve the ship management level of maritime shipping companies.Find the abnormal navigation status of the ship as soon as possible and adjust the route to prevent the occurrence of ship accidents.

关 键 词：航行轨迹 云分段 最优熵 AIS 

分 类 号：U612.22[交通运输工程—船舶及航道工程]