Research on financial crisis warning model based on BP neural network:taking the CATL as an example
With the development of the new energy industry,lithium battery enterprises have become a focus of attention in recent years.To ensure the better development of lithium battery enterprises,this article takes the financial data of 28 listed lithium battery companies from 2018 to 2022 as the research object,uses factor analysis to select 16 representative warning in-dicators,and constructs a BP neural network model for financial crisis warning;Taking CATL,a giant enterprise in the lithi-um battery industry,as an example,a case study was conducted using the efficiency coefficient method combined with actual situations.The results show that the BP neural network financial crisis warning model for the lithium battery industry con-structed in this article has an accuracy rate of 82.6％,which is relatively high and consistent with the actual situation analysis of specific cases.It has strong practicality and can accurately identify the financial crisis situation of lithium battery enterprises and provide early warning.
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