Abstract
When acquiring the risk data, the enterprise financial risk early warning system is easily influenced by the noise data, which leads to the early warning error and low warning accuracy. In order to solve this problem, a financial risk early warning system based on catastrophe progression method is designed. S3C2440A microprocessor is used as the core control module in the hardware part. In the software part, the abrupt progression method is used to mine the abnormal running state, calculate the correlation of the financial data of the risk state, and design the risk warning system after setting the residual value of risk warning. Experimental results show that the average response time of the risk early warning system is about 45 ms, and the accuracy is about 94%.
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Hou, B., Ma, Cs. (2021). Enterprise Financial Risk Early Warning System Based on Catastrophe Progression Method. In: Fu, W., Xu, Y., Wang, SH., Zhang, Y. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-030-82562-1_14
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DOI: https://doi.org/10.1007/978-3-030-82562-1_14
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