Title: Financial risk early warning method for modern manufacturing enterprises based on RBF neural network

Authors: Yanyan Cao

Addresses: College of Architecture, Xinxiang Vocational and Technical College, Xinxiang, 453006, China

Abstract: To detect potential financial risks in advance, reduce the rate of missed and false alarms in risk warning, and improve the accuracy of warning, a modern manufacturing enterprise financial risk warning method based on RBF neural network is proposed. Firstly, network coding methods are used to collect financial data such as total asset turnover rate, current ratio, and net profit margin of modern manufacturing enterprises. Secondly, the K-nearest neighbour method is used to remove outliers from the above data to improve the accuracy of risk warning results. Finally, based on the financial data of modern manufacturing enterprises and the financial risk warning results, a financial risk warning model is constructed using RBF neural network to achieve financial risk warning. The research results indicate that the method has low false positives and false positives rate, and a high F₁ value, which is beneficial for improving the accuracy and effectiveness of enterprise management decisions.

Keywords: RBF neural network; modern manufacturing enterprises; financial risk warning; network coding; K-nearest neighbour method.

DOI: 10.1504/IJMTM.2025.145936

International Journal of Manufacturing Technology and Management, 2025 Vol.39 No.3/4/5, pp.183 - 194

Received: 08 Nov 2023
Accepted: 03 Jun 2024
Published online: 30 Apr 2025 *

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