A Study Of The Mineral Industry Listed Companies’ Financial Risk Prediction Based On BP Neural Network

Mining industry as a head of the whole economy industry, which offers raw materials for all the national people.In importance, and study, analyze, assess, companies in pertinence. Through the view of the mining industry’s special and the financial quality of the listed mining impersonal financial data, reflect all the financial quality of the listed mining companies intuitively, and master the management status of the listed mining companies, and discover the problem time. For protecting the profit of investor, leading the long-term reasonable development has some practical significance. It has both theoretical significance and practical significance for the study on early warning of financial risk of listed mining industry and the professional research of the study on financial risk.This text is based on the positive result of the study on early warning of financial risk from domestic and foreign regard the listed mining companies in China as the research object, from the repayable ability, operation capacity, profitability, cash flow capacity and growth ability this five sides, and detail it into 17 financial index and 1 non-financial index to select the financial original data of 47 enterprises in 2014.Using SPSS to standardize processing and hierarchical cluster analysis detailed the financial risk into some grades and passed the significance text. And structure BP Neural Network Early Warning Model?let financial status in grades offer the accurate output layer target for Early Warning Model. Using direction samples to test, proving the Early Warning Model is in a good effect. It was confirmed by the experimental result that the hierarchical cluster analysis which structured by the listed mining companies—BP neural network financial Early Warning Model is effective.