Financial Performance Management System and Wireless Sharing Network Optimization of Listed Enterprises under BPNN

Abstract

The study aims to respond to the difficulties in establishing an index system in financial performance management and ensuring the security of wireless sharing network and the local extremum and slow convergence speed of the traditional BP neural network (BPNN). First, Levenberg–Marquardt (LM) is used to optimize BPNN, and an improved BPNN is proposed. Second, the financial performance evaluation system of listed companies based on BPNN is constructed. Finally, a wireless network infusion detection system based on the improved BPNN is proposed and tested by constructing datasets and a real test environment. The results show that (1) the financial performance evaluation system of listed enterprises constructed can evaluate the financial performance of listed enterprises with fewer errors. It is easy to operate, and it has high accuracy and the abilities of self-learning and self-adaptation; (2) Wireless Infusion Detection System (WIDS) based on the improved BP algorithm has a high detection rate and a low error rate. The study provides important technical support for listed enterprises to improve the financial performance management level and market competitiveness and strengthen the security protection of networks.