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ABSTRACT
Financial management is an important part of enterprise management, aiming to ensure the reasonable utilization of financial resources and help enterprises achieve business goals. This study utilizes chaotic particle swarm optimization algorithm to optimize the backpropagation neural network, and based on this, constructs a financial management early warning model for enterprise circular economy. Performance testing experiments show that the error reaches the target accuracy of 0.042881, with an R-value of 0.92287, indicating high prediction accuracy of the model; In the comparison experiment with the backpropagation model and the genetic feedback model, this study constructed a model with faster convergence speed and an overall accuracy of 92%, significantly higher than the other two models, further verifying the superiority of the chaotic particle swarm feedback neural network model. This indicates that the research model has certain application value in the financial management of circular economy in enterprises.
Graphical Abstract
Financial risk early warning model (EWM) usually include two basic parts: warning indicators and simulation scenarios. Early warning indicators offer insight into the financial status of investment schemes, which may include return on investment, asset turnover, and earnings per share, among others. A variety of indicators can effectively represent the financial state of a company. This study will provide a detailed introduction to the indicator system of the financial management (FM) EWM. Before constructing an EWM indicator system, it is essential to first classify the financial risk levels.
Disclosure statement
The author has no relevant financial or non-financial competing interests to report.
Additional information
Notes on contributors
Jinlan Jiao
Jinlan Jiao works in Jiangsu Vocational College of Finance and Economics, and obtained a Bachelor of Management degree from Jiangsu University of Science and Technology in 2008. He is a senior accountant, and his main research direction is enterprise financial management and financial risk management.