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    唐国磊

    • 副教授     博士生导师   硕士生导师
    • 主要任职:PhD supervisor
    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:水利工程系
    • 学科:港口、海岸及近海工程
    • 办公地点:综合实验3#410室
    • 联系方式:tangguolei@dlut.edu.cn
    • 电子邮箱:tangguolei@dlut.edu.cn

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    Ship arrival prediction and its value on daily container terminal operation

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    论文类型:期刊论文

    第一作者:Yu, Jingjing

    通讯作者:Tang, GL (reprint author), Dalian Univ Technol, Fac Infrastruct Engn, State Key Lab Coastal & Offshore Engn, Dalian 116023, Liaoning, Peoples R China.

    合写作者:Tang, Guolei,Song, Xiangqun,Yu, Xuhui,Qi, Yue,Li, Da,Zhang, Yong

    发表时间:2018-06-01

    发表刊物:OCEAN ENGINEERING

    收录刊物:SCIE、EI

    卷号:157

    页面范围:73-86

    ISSN号:0029-8018

    关键字:Arrival prediction; Late/early arrivals; Data mining; Container terminal operation; Berth allocation; Quay crane assignment

    摘要:Effective prediction of ship arrivals should provide the estimated delay or advance of arrival ships with greater accuracy, and improve the performance of container terminal operations. Therefore, taking Gangji (Yining) Container Terminal (GYCT), China, as an example, this paper resorts to data mining approaches to predict ship arrivals and explore the value of such predicted ship arrivals on the container terminal operation. First, this study applies three data mining approaches, including Back-Propagation network (BP), Classification and Regression Tree (CART) and Random Forest (RF), to estimate the delay or advance of ship arrivals using the collected data of ship arrivals. Then the predictive performance of these three approaches is compared and discussed, it is concluded that RF performs better than BP and CART, and ETA month and ship length are the most important determinants of ship arrivals in GYCT terminal. Finally, series simulation experiments are conducted to assess the value of the ship arrivals predicted by RF model on the improvement on daily operation planning of berth allocation and quay crane assignment in the GYCT terminal. And the results show that incorporating the predicted ship arrivals by RF model is beneficial to improve the performance of operation planning of GYCT terminal.