Research on dynamic early warning of enterprise financial risk based on particle swarm optimization

In order to better solve the phenomenon that the number of abnormal financial conditions of listed companies increases year by year, the report examines listed companies to improve the risk prevention risk of listed companies and maximize the effectiveness of early warning of financial risks to list...

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Bibliographic Details
Published in:Procedia computer science 2024, Vol.243, p.1162-1172
Main Author: Li, Xinhua
Format: Article
Language:English
Subjects:
Financial risk warning
Listed company
Particle swarm optimization
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Summary:In order to better solve the phenomenon that the number of abnormal financial conditions of listed companies increases year by year, the report examines listed companies to improve the risk prevention risk of listed companies and maximize the effectiveness of early warning of financial risks to listed companies. Early warning based on the financial risk of listed companies is formed by the integration of financial risk management early warning, risk management affects the thinking, particle optimization algorithms and neural network related theoretical algorithms. At the same time, a more efficient financial estimation model has been improved by the analysis of the core material and the particle herd optimization algorithm to improve the accuracy of the financial performance risk. The final comparison shows that the accuracy of the risk assessment model developed in this article has increased from 76% to 86% compared to the standard estimates, and the accuracy of higher demand standards.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2024.09.137