Early warning of enterprise decline in a life cycle using neural networks and rough set theory

Early warning of whether an enterprise will fall into decline stage in a near future is a new problem aroused by the enterprise life cycle theory and financial risk management. This paper presents an approach by use of back propagation neural networks and rough set theory in order to give an early warning whether enterprises will fall into a decline stage. Through attribute reduction by rough set, the influence of noise data and redundant data are eliminated when training the networks. Our models obtained favorable accuracy, especially in predicting whether enterprises will fall into decline or not.