Financial Distress Prediction Of Chinese Listed Enterprises Of Manufacturing Industries Based On BP Neural Networks

With the arrival of the new normal economy in our country,manufacturing enterprises are confronted with new challenges.The financial crisis,for any enterprise,directly decides its survival or the fate of destruction.Therefore,it is of great practical significance to study the financial crisis of enterprises.The manufacturing industry,which occupies more than 40% of our GDP,is undoubtedly the mainstay of our economy.The sustainable development of manufacturing industry can directly affect the sustainable development of our economy.Along with the "China Manufacturing 2025" and "supply-side reform" policy,China's manufacturing industry will face a new bloody.At the same time,the production level is rising,the backward production capacity will be annihilated in the history of the Rolling River.Although "China made" the world's leading,but on the one hand the impact of the 2008 global financial crisis,on the other hand by the continuous development of China's market economy,manufacturing enterprises faced with many challenges,slightly inadvertently will be moved forward the torrent of the financial situation of the enterprise is of great significance.Based on BP artificial neural network as the main model,this paper constructs a financial pre-warning model for the listed manufacturing enterprises of China's motherboard.In the sample selection,the article selects the same subdivision industry,the scale approximate,the same time node 45 St Enterprise and 45 non-ST manufacturing listed company as the research sample,for the BP Neural Network study training.The paper also screened 24 indexes in financial statements and outside the table,which improved the rationality of the financial pre-warning Index system.And the financial indexes are used to train the BP neural network data model.Finally,the BP neural network is tested with the financial data of “Zhejiangzhenyuan”.It is found that the prediction method based on BP neural network has full advantage of fault tolerance and self-learning habit of artificial neural network,and has good predictive accuracy and applicability.”Zhejiangzhenyuan” passes the model test,the current financial situation is good.