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The application research of application decision model based on internet of things in enterprise supply chain management

机译:基于企业供应链管理中的应用互联网应用决策模型的应用研究

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摘要

There are many problems in the supply chain management of Chinese enterprises, which restricts the development of enterprises and the improvement of benefits. In order to improve the decision-making ability of Internet of Things (IoT) applications in enterprise supply chain management, the collaborative filtering algorithm is optimized The algorithm determines the collaboration type according to the nature of the optimization target, and calculates the user similarity based on the user browsing behavior, so as to seek the recommendation function of the user to best evaluate the individual. According to the two objectives of the shortest time and the highest overall satisfaction in emergency dispatching in enterprise supply chain management, a two-level planning model of commodity scheduling is constructed, the time function of the supply chain delivery process calculated. The simulation results of the model show that the demand forecasting algorithm based on neighborhood rough set and GA-SVM is used to predict the demand of chain retail supply chain, which achieves high prediction accuracy. The maximum error is 5.71%, the minimum error is 0.60. The average error is %, which is 2.84%. The research in this paper has implications for enterprise application of IoT in supply chain management. The use of decision-making model can greatly improve the operational efficiency of the supply chain.
机译:中国企业供应链管理有很多问题,这限制了企业的发展和改善福利。为了改善企业供应链管理中的事物互联网的决策能力(IOT)在企业供应链管理中,优化了协作滤波算法,算法根据优化目标的性质确定协作类型,并计算基于用户的相似度在用户浏览行为上,以便寻求用户的推荐功能,以最佳地评估个人。根据最短时间和在企业供应链管理中紧急派遣的最短时间的两个目标,建设了两级商品调度规划模型,计算了供应链递送过程的时间函数。该模型的仿真结果表明,基于邻域粗集和GA-SVM的需求预测算法用于预测链零售供应链的需求,从而实现了高预测精度。最大误差为5.71%,最小误差为0.60。平均误差为%,即2.84%。本文的研究对IoT在供应链管理中的企业应用有影响。决策模型的使用可以大大提高供应链的运行效率。

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