Information system operational efficiency prediction algorithm based on deep learning
Xiaofeng Gao, Dayong Chang, Yongqiang Guo, Du Wang · International Journal of Grid and Utility Computing · 2024
This article aims to use deep learning algorithms to accurately predict and analyse the operational efficiency of enterprise information systems, provide key management insights and decision support for enterprises. This article applies deep learning technology to predict the operational efficiency of enterprise information systems, uses Back Propagation Neural Network (BPNN) and Deep Belief Network (DBN) to analyse the total assets, operating expenses, investment expenses, operating revenue, operating profits, and other data of enterprises, in order to predict the operational efficiency of enterprises. This article trained data from five retail listed companies in the Chinese A-share market, and the results showed that the average prediction accuracy of operating efficiency using BPNN algorithm was 97.72%, while the average prediction accuracy of operating efficiency using DBN algorithm was 98.88%. The DBN algorithm has good computational efficiency and predictive performance in enterprise information system data analysis.