Application of BP Neural Network Model in the Operational Risk Early Warning System of Listed Electric Power Enterprises
Aiming at the low accuracy of the current financial risk early warning of electric power enterprises,the study uses FOA to optimize BP neural network,and constructs a financial risk early warning model for listed electric power enterprises on the basis of determining the financial risk index evaluation system,and the evaluation indicators are cash flow,growth ability,operational ability,debt servicing ability,profitability and market dimensions.In the financial crisis prediction of three types of enterprises:normal enterprises,mild financial crisis and severe financial crisis,the accuracy rates of TOA-BP neural network are 92.31％,91.67％and 91.67％,respectively.It is proved that the proposed enterprise financial evaluation system and fore-casting model have high degree accuracy,and can be applied to the financial risk control of enterprises.
BP neural networkFOAelectric power enterpriseoperational riskearly warning
万方数据
维普
