Study of Financial Risk Prediction Based on Rough Set-ANN Model

摘要

This article combines rough set and artificial neural network (ANN) which is improved with momentum accession and parameter self adaptive algorithm, and constructs a new financial risk prediction model. We apply this model to the empirical research on the financial risk prediction of some Chinese listed companies. Then we compared the outcome with the standard BP ANN, the results show that this combination model has higher prediction precision and efficiency than the traditional BP ANN model.