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Quay Crane Allocation of Container Terminal Based on Cluster Analysis

机译:基于聚类分析的集装箱码头码头起重机分配

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摘要

Quay crane allocation is one of the most important scheduling plans in the container terminal. A large of production data is stored in the database of the terminal. This paper utilizes the method of data mining to analyze the problem of quay crane allocation by using these data. From the mining, valuable information has been gotten from the database. The paper chooses the fuzzy c-means cluster algorithms to study the data of quay crane allocation in database. Data mining model of quay crane allocation has been designed by learning plan of quay crane in order to improve the production efficiency of container terminals. And the case study shows that the method using in the paper is effective.
机译:码头起重机的分配是集装箱码头最重要的调度计划之一。大量生产数据存储在终端的数据库中。本文利用数据挖掘的方法,利用这些数据来分析码头起重机的配置问题。通过挖掘,从数据库中获得了有价值的信息。本文选择模糊c-均值聚类算法研究数据库中码头起重机分配数据。根据码头起重机的学习计划,设计了码头起重机分配的数据挖掘模型,以提高集装箱码头的生产效率。实例研究表明本文所采用的方法是有效的。

著录项

  • 来源
    《Journal of software 》 |2013年第5期| 1201-1208| 共8页
  • 作者单位

    Container Supply Chain Technology Engineering Research Center of MOE,Shanghai Maritime University, Shanghai, 201306, P. R. China,College of Mechanical Engineering, Tongji University, Shanghai, 201804, P. R. China;

    Container Supply Chain Technology Engineering Research Center of MOE,Shanghai Maritime University, Shanghai, 201306, P. R. China;

    College of Mechanical Engineering, Tongji University, Shanghai, 201804, P. R. China;

    Container Supply Chain Technology Engineering Research Center of MOE,Shanghai Maritime University, Shanghai, 201306, P. R. China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    container terminal; quay crane allocation; fuzzy c-means algorithms; cluster analysis;

    机译:集装箱码头;码头起重机分配;模糊c均值算法;聚类分析;

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