基于BP-SVM算法的中大型企业财务危机预警系统  

Financial Crisis Early Warning System of Medium and Large Enterprises Based on BP-SVM Algorithm

作　　者：夏瑶 XIA Yao(School of International Education,Wanjiang University of Technology,Maanshan 243000,China)

机构地区：[1]皖江工学院国际教育学院,安徽马鞍山243000

出　　处：《西安文理学院学报（自然科学版）》2023年第1期17-20,共4页Journal of Xi’an University(Natural Science Edition)

基　　金：安徽省教育厅重点项目(SK2020A0647)。

摘　　要：为了提高中大型企业财务危机预警的精度,提出了基于BP-SVM算法的中大型企业财务危机预警系统研究.硬件设计中,根据传感器内部电路,结合企业财务危机数据分类的CPU板卡设计中大型企业财务危机报警器.软件设计中,利用BP-SVM算法计算出财务危机数据的聚类中心,检测出大型企业财务系统的异常行为,实现了企业财务危机的预警.测试结果表明,文中系统在中大型企业财务危机预警中的功能满足用户的要求,通过将吞吐量控制在800 bps~1000 bps之间,预警精度提高到90%以上.In order to improve the accuracy of financial crisis early warning of medium and large enterprises,the research on financial crisis early warning system of medium and large enterprises based on BP-SVM algorithm is proposed.In the hardware design,according to the internal circuit of the sensor,combined with the CPU card of the enterprise financial crisis data classification,the medium and large enterprise financial crisis alarm is designed.In the software design,BP-SVM algorithm is used to calculate the cluster center of financial crisis data,detect the abnormal behavior of large enterprise financial system,and realize the early warning of enterprise financial crisis.The test results show that the functions of the system in the financial crisis early warning of medium and large enterprises meet the requirements of users.By controlling the throughput between 800 bps and 1000 bps,the early warning accuracy is improved to more than 90%.

关 键 词：BP-SVM算法 财务危机 数据采集 预警系统 异常行为 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术] F275[自动化与计算机技术—计算机科学与技术] F832.51[经济管理—企业管理]