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    航运大数据的应用现状及其发展趋势

    摘要

    航运作为一个既古老又现代、高技术重资产的传统行业,随着信息技术互联网的应用与发展,正面临大数据、人工智能等新兴技术的冲击与洗礼。航运业包括船舶运输企业、港口码头等核心生产部门,也包括船代、货代、仓储、物流等辅助业务部门以及监管服务部门等。所有这些航运核心业务、辅助生产、监管服务等企业部门产生的业务数据、生产信息数据、监管服务数据、海洋环境数据等集合成航运大数据。本文简要分析了航运大数据的分类、特点,并从航运企业、监管部门、第三方服务企业、电商平台等不同视角介绍了航运大数据的发展应用现状以及当前存在的问题和挑战,并对航运大数据及航运业的发展趋势进行了分析与展望。

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    Abstract

    As a traditional industry with both ancient and modern,high-tech and heavy assets,shipping is facing the challenge of emerging technologies such as big data and artificial intelligence with the application and development of information technology Internet.It is not only an important issue in shipping industry,but also of great significance to build a socialist country to solve how to deal with the influence of big data,and develop efficient and intelligent shipping industry by using big data.The shipping industry includes the core production departments such as ship transportation enterprises and port terminals,as well as auxiliary business departments such as ship agent,freight agent,warehousing and logistics,and supervision service departments.All business data of the shipping core business,auxiliary production,supervision services,etc.,of production information,regulatory service,and marine environment etc.forms big data of the shipping.The paper briefly analyzes the classification and characteristics of the big data of shipping,and introduces the development and application status of big data of shipping from the different perspectives of shipping companies,supervision authorities,third-party service enterprises,e-commerce platforms,as well as current problems and challenges. Also,the report analyzes and predicts the trend of big data of shipping in the future.

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    作者简介
    王晓峰:王晓峰,教授,工学博士,交通信息工程与控制专业博士生导师,上海海事大学信息工程学院院长,上海海事大学学报编委,International Journal of Granular Computing,Rough Sets and Intelligent Systems (IJGCRSIS)编委,兼任中国人工智能学会机器学习专业委员会常务委员,中国人工智能学会智能交通专业委员会委员,粗糙集与粒度计算专业委员会委员。
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