融合物联网与数据挖掘的物流信息处理与分析

Logistics Information Processing and Analysis by IOT and Data Mining

文章针对物流信息采集、跨组织管理、决策支持三方面的突出问题,提出应采纳融合物联网、数据挖掘等新兴技术的综合解决方案。综合应用物联网与数据挖掘及其互补性,构建了融合物联网与数据挖掘的物流信息处理与分析模型,主要包括:基于物联网的物流信息感知与采集、基于粗糙集与证据理论的物流信息整合处理、基于粗糙集与神经网络的物流信息分析。进而,以冷链物流信息管理为背景,设计了融合物联网和粗糙集的物流信息处理和分析流程,从而为动态、离散的物流信息处理与分析提供了有效解决方案。

In order to solve the problems of logistics information collection, inter-organizational management and decision-support, the study proposes an integrated solution of Internet of things （IOT） and data mining. Then, the study constructs a logistics information processing and analysis model by analyzing IOT, data mining and complementarities between them. The model is composed of three parts： logistics information sensing and gathering by IOT, logistics information integrating and processing by rough set and DS theory, logistics information analysis by rough set and artificial neural networks. Finally, a logistics information processing and analysis process is designed for cold chain based on IOT and rough set to provide a solution to process and analyze dynamic and discrete logistics information.