Abstract

With the rapid growth of my country’s market economy and the reform of the management system, the risks in company investment and financial operations have gradually become prominent. In the thesis, the financial status risk early warning model of digital companies based on the kernel function adjustment algorithm is studied, and the relevant theoretical knowledge about the financial status risk of digital companies is understood on the basis of literature data, and then the digital company that adopts the kernel function adjustment algorithm. The financial status risk early warning model is established, and the newly established model is tested. According to the experimental conclusions, it is concluded that the improved algorithm studied in this paper is better than PCA-SVM in reducing the number of support vectors.

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