Financial management early warning model of enterprise circular economy based on chaotic particle swarm optimization algorithm

Abstract

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.