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Financial accounting intelligence management of internet of things enterprises based on data mining algorithm

机译:基于数据挖掘算法的东西企业财务会计情报管理

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With the introduction of the information age, enterprise financial management has been challenged as never before, and the application of Internet of Things (IoT) technology can effectively improve the efficiency of financial accounting management and realize the informationization of financial management. In order to solve the problem of enterprise financial accounting data processing, a data mining algorithm is constructed, which uses data mining technology to obtain massive information data and cluster analysis processing to realize the fusion of multiple uncertainty information processing models. Firstly, the financial information cloud platform is designed by using the IoT technology. The financial risk index coefficient of the enterprise is judged by the association rules. Finally, the research sample is divided into the risk group and the normal group according to the ST classification standard, and the 296 financial indicators of the two groups are correlated. The research results show that if the enterprise with a score below 40 points has financial risk, the accuracy rate is 70.9%, which is slightly lower than the financial risk warning model of the decision tree. Through the research of this paper, it has enlightenment to the financial accounting management of IoT enterprises. The data mining technology is applied in the processing of massive data information of accounting, which is more efficient.
机译:随着信息时代的推出,企业财务管理已被挑战,从未以前则受到挑战,而互联网的应用(IOT)技术可以有效提高财务会计管理效率,并实现财务管理信息化。为了解决企业财务核算数据处理的问题,构造了一种数据挖掘算法,它使用数据挖掘技术来获得大规模信息数据和集群分析处理,以实现多个不确定性信息处理模型的融合。首先,金融信息云平台是通过使用物联网技术设计的。企业的财务风险指数系数由协会规则判断。最后,根据ST分类标准,研究样本分为风险组和正常组,两组的296个财务指标是相关的。研究结果表明,如果企业得分低于40分,则具有财务风险,准确率为70.9%,略低于决策树的金融风险警告模型。通过本文的研究,它对物联网企业的财务会计管理有启示。数据挖掘技术应用于处理的大规模数据信息,这更有效。

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