复杂环境中高可用船舶AIS大数据信息处理方法  

High-availability ship AIS big data information processing method in complex environment

作　　者：周雪芳[1] 刘树龙[1] 周海龙 ZHOU Xue-fang;LIU Shu-long;ZHOU Hai-long(Qingdao Huanghai University,Qingdao 266500,China;Qingdao Beihai Shipbuilding Industry Co.,Ltd.,Qingdao 266520,China)

机构地区：[1]青岛黄海学院,山东青岛266500 [2]青岛北海船舶重工有限公司,山东青岛266520

出　　处：《舰船科学技术》2022年第6期137-140,共4页Ship Science and Technology

基　　金：青岛市源头创新计划应用基础研究项目(18-2-2-41-jch)。

摘　　要：提升复杂通航环境下船舶航行安全性,提出复杂环境中高可用船舶AIS大数据信息处理方法。选取分布式架构作为船舶AIS大数据的信息处理架构,采集船舶AIS数据,对数据实施报文解析处理,利用云计算节点将完成AIS大数据传送至Oracle数据库。Oracle数据库采用同步复制技术,利用Markov链建立可用性评估模型,依据可用性评估结果确定分布式数据库的最佳接管方案,提升AIS大数据的可用性。选取Dbscan算法完成数据聚类,数据聚类结果为舰船目标识别等应用提供数据基础。实验结果表明,该方法可以有效处理船舶AIS大数据,数据聚类的类内相似度高于0.93,信息处理可用性高。To improve the navigation safety of ships in complex navigation environment,a high availability ship AIS big data information processing method in complex environment is proposed.Select the distributed architecture as the information processing architecture of ship AIS big data,collect ship AIS data,analyze and process the data,and use the cloud computing node to transmit the completed AIS big data to the Oracle database.The Oracle database adopts synchronous replication technology and uses Markov chain to establish the availability evaluation model.According to the availability evaluation results,determine the best takeover scheme of distributed database,improve the availability of AIS big data,select Dbscan algorithm to complete data clustering,and the data clustering results provide data basis for ship target recognition and other applications.Experimental results show that this method can effectively deal with ship AIS big data,the intra class similarity of data clustering is higher than 0.93,and the availability of information processing is high.

关 键 词：复杂环境 船舶 AIS大数据 DBSCAN算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]