Research on enterprise financial economics early warning based on machine learning method

Article type: Research Article

Authors: Yi, Jian

Affiliations: Department of Economic Management, Sichuan TOP IT Vocational Institute, Chengdu, Sichuan, China | E-mail: yj17h8@126.com

Correspondence: [*] Corresponding author: Department of Economic Management, Sichuan TOP IT Vocational Institute, Chengdu, Sichuan, China. E-mail: yj17h8@126.com.

Abstract: The stability of the economic market is an important factor for the rapid development of the economy, especially for the listed companies, whose financial and economic stability affects the stability of the financial market. It is helpful for the healthy development of enterprises and financial markets to make an accurate early warning of the financial economy of listed enterprises. This paper briefly introduced the support vector machine (SVM) and back-propagation neural network (BPNN) algorithms in the machine learning method. To make up for the defects of the two algorithms, they were combined and applied to the enterprise financial economics early warning. A simulation experiment was carried out on the single SVM algorithm-based, single BPNN algorithm-based, and SVM algorithm and BPNN algorithm combined model with the MATLAB software. The results show that the SVM algorithm and BP algorithm combined model converges faster and has higher precision and recall rate and larger area under the curve (AUC) than the single SVM algorithm-based model and the single BPNN algorithm-based model.

Keywords: Machine learning, early financial warning, combined model, back-propagation

DOI: 10.3233/JCM-215783

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 2, pp. 529-539, 2022