Financial Crisis Warning Model based on BP Neural Network
基于BP神经网络的上市公司财务预警模型

The paper uses the BP artificial neural network to establish a model of financial crisis warning for the purpose of testing the accuracy of the methods used for financial crisis warning. The model's sample is consisted of the cross section financial indexes of 120 listed companies of which 60 companies is used as a testing sample. After repeated training and studying of the samples, we got a distinguishing-positive rates of 90.8% to the sample model setting and 90% to the testing sample.. This is a large improvement to the predicting precisions,in comparison with main-composition analysis which has got a percentage of 90 to the first sample and 81.7 to the later by using the same samples. The study indicates that BP neural network is a model without linear mapping, high in correlation among indexes, changing non-line and that a relatively satisfying outcome can be gotten even if the data are not complete or lacking. So it's a relatively optimum method used for forecasting, with wide applying area and high value of popularizing.