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Research on Logistics Management Information System Based on Big Data

机译:基于大数据的物流管理信息系统研究

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To transform data into wealth more efficiently in a variety of databases, to realize the intelligent real-time monitoring of logistics data, this paper discusses the application of data mining in logistics information system by describing the development status of logistics industry in the era of big data. Firstly, the basic components, construction modules and working mechanism of Hadoop ecosystem are deeply analyzed and studied; the standard process of big data mining process is analyzed and the design idea and process of traditional K-means algorithm are deeply studied and improved. Through the construction of Hadoop cloud computing platform and the analysis of customer transaction volume, profit, order quantity and credit degree and other data and characteristics, the feasibility and effectiveness of the improved algorithm applied to Hadoop cloud computing platform is verified, combined with other industry data evaluation and analysis experience. The results show that the improved scheme has obvious advantages in big data processing, which provides a new technical means for optimizing logistics management and improving statistical efficiency.
机译:要在各种数据库中更有效地将数据变为财富,以实现物流数据的智能实时监控,本文讨论了数据挖掘在物流信息系统中的应用,描述了物流业在大型时代的发展现状数据。首先,对Hadoop生态系统的基本组件,构造模块和工作机制深受分析和研究;分析了大数据挖掘过程的标准过程,并深受研究和改进了传统K-MEAS算法的设计理念和过程。通过建设Hadoop云计算平台和对客户交易量的分析,利润,订单数量和信用度等数据和特点,验证了应用于Hadoop云计算平台的改进算法的可行性和有效性,与其他行业相结合数据评估和分析经验。结果表明,改进的方案在大数据处理方面具有明显的优势,提供了一种用于优化物流管理和提高统计效率的新技术手段。

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