极地研究

极地研究 ›› 2020, Vol. 32 ›› Issue (1): 102-111.DOI: 10.13679/j.jdyj.20190010

• 研究论文 • 上一篇    下一篇

北极水域船舶事故特征及关联规则分析

付姗姗1,2, 刘燕平1, 席永涛3, 万辉4   

  1. 1.上海海事大学交通运输学院, 上海 200136;
    2.内河航运技术湖北省重点实验室, 湖北 武汉 430063;
    3.上海海事大学商船学院, 上海 201306;
    4.东海航海保障中心上海海图中心, 上海 200090
  • 收稿日期:2019-02-26 修回日期:2019-05-16 出版日期:2020-03-30 发布日期:2020-03-30
  • 通讯作者: 席永涛
  • 基金资助:
    国家自然科学基金(51709168)、上海市科技创新行动计划(19692106500, 18DZ1206104)、内河航运技术湖北省重点实验室基金(NHHY2018001)资助

Feature analysis and association rule mining of ship accidents in Arctic waters

Fu Shanshan1,2, Liu Yanping1, Xi Yongtao3, Wan Hui4   

  1. 1.College of Transport and Communications, Shanghai Maritime University, Shanghai 200136, China;
    2.Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063; China;
    3.Merchant Marine College, Shanghai Maritime University, Shanghai 200136, China;
    4.Shanghai Chart Center, Donghai Navigation Safety, Shanghai 200090, China
  • Received:2019-02-26 Revised:2019-05-16 Online:2020-03-30 Published:2020-03-30
  • Contact: Yong-Tao XI

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摘要： 北极海冰的大量融化, 加速了北极航道开发和利用, 对北极水域船舶事故风险管理提出了更高的要求。本文以2008—2017年的北极水域船舶事故数据为样本, 运用数据挖掘技术和方法, 对北极水域船舶事故进行了时空特征分析, 并对船舶属性与事故属性之间的潜在映射关系进行了关联规则挖掘。结果表明: 北极水域事故数逐年呈上升的趋势, 事故主要发生在巴伦支海东部的俄罗斯摩尔曼斯克港口水域和挪威北部水域; 北极水域严重事故受船舶总吨、船旗国、船舶类型、事故类型、事故水域等变量的影响, 船舶尺度较大的船舶更容易造成严重事故; 北极水域俄罗斯籍渔船的严重事故, 很多是由机损事故引发的, 但很少造成环境污染。研究结论可辅助海事管理部门和航运企业开展北极水域船舶事故预防和风险管理工作。

关键词: 北极航运, 船舶事故特征分析, 数据挖掘, 时空分析, 关联规则

Abstract: With the melting of sea ice, Arctic sea routes are increasingly used and developed, requiring information to support the management of risks of ship accidents in Arctic waters. We identified latent association rules between ship and accident attributes using accident records from 2008 to 2017, data mining and temporal and spatial analysis. Results show that the number of accidents has been increasing, with most accidents occurring in the harbor of Мурманск in eastern Barents Sea and in northern Norwegian Sea. The small Russian fishing vessel is the dominant vessel type in Arctic waters. Serious accidents in Arctic waters are influenced by several variables such as gross tonnage, flag, vessel type, accident type and accident location. Large ships are more likely to cause serious accidents. Serious accidents of Russian fishing vessels in Arctic waters were often caused by machinery damage, and rarely caused environmental pollution. These findings can be of use to maritime safety administrations and shipping companies in the prevention of accident and risk management of Arctic shipping.

Key words: Arctic shipping, feature analysis of maritime accidents, data mining, spatio-temporal analysis, association rule