Research Of Financial Crisis Prevention Of Manufacturing Listed Company Based On Gray Neurology Network

With the rapid development of global economy, manufacturing, as the most important one in the real economy, has become the crucial strength for national development, and has played an important role in economic development of each country. Due to the rapid development of economic theory and the continuous progress of financial tools, enterprises have got more freedom in aspect of financing and investing, meanwhile, the enterprises have faced more risks and no-confirmative factors for development. Manufacturing enterprises are no exception, together with the furious competition from global manufacturing, the manufacturing enterprises also will meet different non-confirmative factors during their production and operation activities. Once enterprises cannot prevent the risks, they will meet risks or even bankruptcy. Under these conditions, the profit-relevant people of enterprises shall concern the prediction of financial crisis, and take it as one of the major risks. To establish an efficient and accurate financial alarming model has an important meaning for the managers to prevent operative risks, investors to make right decisions for investment, government to optimize resources, debtors to guarantee the safety of securities and so on, as well as the employees’salaries.This article has summarized the references and research outcomes relevant to financial crisis alarming of foreign and domestic enterprises, based on this, firstly, A share of Hu and Shen listed companies, it has chosen 87 enterprises which meet financial crisis compared with 261 enterprises which have healthy financial system from; secondly, it has chosen 27 financial indicators and 14 non-financial indicators according to the principles of relativity, prediction, completeness and adaptability, then, take use of gray relevant analysis and fuzzy comprehensive evaluation method to deal with each financial indicator and non-financial indicator; finally, in order to establish a dynamic financial alarming model, this article brings the predicted data of gray prediction model into the optimized neurological network model to build gray neurological network, this model has combined the advantages of gray prediction model with those of neurological network model, through simulating the predicted results, it has successfully judged the financial crisis and health of listed manufacturing enterprises, offering an important principle for managers to know about financial condition and prevent financial crisis.The research results show that:(1) Relatively less financial index could effectively reflect whether the enterprise falls into financial crisis. (2) The utilization of the Fuzzy Comprehensive Evaluation could effectively deal with the non-financial index, elevating the computing speed of the model, reducing the cost for human calculation. (3) Gray neural network model established by the series connection of Grey system theory, theory of fuzzy comprehensive evaluation and BP neural network is a good dynamic forewarning model. (4) Through the empirical analysis of the forewarning samples, the forewarning model of gray neural network could provide the managers with relevant financial status of the public companies in manufacturing industry, helping the enterprise’s mangers make right decisions towards various risky financial status in order to guarantee the normal performance of the enterprises.