| 面向海运统计的AIS大数据挖掘分析研究 |
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| 引用本文： | 赵龙飞,姜晓轶,孙苗,曹磊,郭雪,吕憧憬.面向海运统计的AIS大数据挖掘分析研究[J].海洋科学,2021,45(12):55-64. |
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| 作者姓名： | 赵龙飞 姜晓轶 孙苗 曹磊 郭雪 吕憧憬 |
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| 作者单位： | 国家海洋信息中心,天津 300171;自然资源部海洋信息技术创新中心,天津 300171 |
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| 基金项目： | 国家重点研发计划（2017YFC1405300） |
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| 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.
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| 关 键 词： | 海运统计 大数据 海洋经济 AIS 挖掘分析 |
| 收稿时间： | 2020/12/16 0:00:00 |
| 修稿时间： | 2021/3/2 0:00:00 |
AIS big data mining for maritime statistics |
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| ZHAO Long-fei,JIANG Xiao-yi,SUN Miao,CAO Lei,GUO Xue,L&#; Chong-jing.AIS big data mining for maritime statistics[J].Marine Sciences,2021,45(12):55-64. |
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| Authors: | ZHAO Long-fei JIANG Xiao-yi SUN Miao CAO Lei GUO Xue L&#; Chong-jing |
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| Institution: | National Marine Data and Information Service,National Marine Data and Information Service,National Marine Data and Information Service,National Marine Data and Information Service,National Marine Data and Information Service,National Marine Data and Information Service |
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| Abstract: | In order to solve the problems of poor data quality, poor timeliness, outdated statistical products and lack of credibility of traditional statistical methods of maritime industry, a method of maritime statistics based on AIS big data mining analysis is proposed. The technical route of 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. Taking the application of AIS data of global bulk cargo ships from March to May in 2019 as an example, it shows that this method can provide big data statistical indicators of port, sea passage and bulk cargo, and provides a new idea for realizing real-time, accurate and refined statistical analysis and presentation of maritime transportation. |
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| Keywords: | Maritime Transport Statistics Big data Marine Economy AIS Mining Analysis |
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