Financial Warning of Listed Company of Information Industry Based on Rough Set and BP Neural Network Model

By combining effectively BP neural network model and attribute reduction algorithm of rough set, this paper studies the prediction of financial crisis in China listed companies of information industry. Select 52 "ST" listed companies and 52 companies that are non-financial difficult companies from the Shanghai and Shenzhen A-share stock market as the sample, using Matlab7.1 software, based on 6 financial ratio indices, building a financial warning system based on BP neural network. The test results show that the accuracy can reach 86.83%, comparing with logistic model, BP neural network model is more effective and accurate in practical application.