大数据价值挖掘在货运行业的应用初探

The Junior Exploration of Big Data Value Mining in Freight Transportation

物流成本高是货车超载、超速现象普遍的内在因素。利用大数据技术对交通数据进行深度分析进而优化货运调配,是提高货运效率、降低物流成本、实现安全运输的全新利器。本文探讨大数据相关技术以及大数据处理平台的构建理论,提出货运行业大数据价值挖掘系统架构。文章在分析货运大数据的来源、内容、类型、处理手段的基础上,对异构货运大数据进行处理整合,深度分析与挖掘,通过货车实时位置及运行轨迹,结合货运单形成货物迁徙图,为货运行业管理、物流企业、交通管理部门、相关服务企业提供具有深度价值行业信息,为行业规划、企业决策、交通监管提供强有力的支持。

Logistics cost is the internal factor of overloading and speeding. In-depth analysis of traffic data using large data technology and optimizing freight allocation, is a new tool to improve efficiency, reduce logistics cost and achieve safe transportation. This thesis discusses the related technologies of the big data as well as data processing platform theory and proposes freight industry data mining system framework.Based on the analysis of the sources, contents, types and processing methods of freight big data, the paper analyzes and integrates the heterogeneous freight data, and thus form a freight migration map through the combination of real-time position and running track of freight vehicles and the freight documents, which provides a valuable industry information for the industry management, logistics enterprises, transportation management departments and related services and also a good assistance to industry planning, enterprise decision-making, traffic regulating.