Data Aggregation Model of Enterprise Financial Supervision Based On BP Neural Network

Abstract

Aiming at the problems of high damping coefficient and long aggregation response time of traditional enterprise financial supervision data aggregation model, an enterprise financial supervision data aggregation model based on BP neural network is designed. In order to effectively gather enterprise financial supervision data, an enterprise model of financial supervision data is proposed based on concurrent workflow. Using the basic financial data, construct the tree workflow, use the financial data summary server tree, construct the multi-level data aggregation mechanism, compress the enterprise financial supervision data based on BP neural network, and realize the model through the tree workflow and multi-level data aggregation mechanism. The experimental results show that the aggregation damping coefficient and response time of the design model are significantly lower than those of the control group, which can solve the problems of high damping coefficient and long aggregation response time of the traditional enterprise financial supervision data aggregation model.