赵龙飞^1,2, 姜晓轶^1,2, 孙苗^1,2, 曹磊^1,2, 郭雪^1,2, 吕憧憬^1,2
1.国家海洋信息中心, 天津 300171;2.自然资源部海洋信息技术创新中心, 天津 300171

摘要:
为解决传统海运产业统计方法数据质量不高、时效性差、统计产品陈旧短缺、公信力不足等的问题，提出基于AIS大数据挖掘分析开展海运统计的方法。详细阐述了基于AIS大数据的海运统计分析技术路线、大数据平台技术架构，以及电子围栏分析、航行事件分析、航次分析和统计指标生成等关键模型算法。以2019年3月至5月全球大宗货品船舶的AIS数据应用为例表明，该方法可提供港口、海上通道和大宗货品三方面的海运大数据统计指标，为实现海运即时化、准确化、精细化的统计分析与展现提供了新思路。
关键词:海运统计大数据海洋经济AIS挖掘分析
DOI：10.11759/hykx20201216003
分类号:TP399
基金项目:国家重点研发计划（2017YFC1405300）

AIS big data mining for maritime statistics
ZHAO Long-fei^1,2, JIANG Xiao-yi^1,2, SUN Miao^1,2, CAO Lei^1,2, GUO Xue^1,2, LÜ Chong-jing^1,2
1.National Marine Data and Information Service, Tianjin 300171, China;2.Marine Information Technology Innovation Center of the Ministry of Natural Resources, Tianjin 300171, China
Abstract:
To address the problems of poor data quality, poor timeliness, outdated statistical products, and the unreliable traditional statistical methods of the maritime industry, a method of maritime statistics based on automatic identification system (AIS) big data mining analysis is proposed in this paper. The technical route of a maritime statistical analysis based on AIS big data, the technical architecture of big data platform, and the key model algorithm of electronic fence analysis, navigation event analysis, voyage analysis, and statistical index generation are elaborated in detail. With the application of AIS data of global bulk cargo ships from March to May in 2019 as an example, this method can provide big data statistical indicators of port, sea passage, and bulk cargo, as well as provide a new idea for realizing real-time, accurate, and refined statistical analysis and presentation of maritime transportation.
Key words:maritime transport statisticsbig datamarine economyAISmining analysis





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