Steel industry is a huge industry group, whose listed companies in this industry as a representative of the industry healthy and overall development, theirs comprehensive strength can represent the overall development trend of the industry. This paper combines the own characteristics of steel-listed companies, builds steel enterprises financial crisis early warning indicator system, defines the superintendent of the financial crisis, and finally establishes steel enterprise financial crisis based on BP neural network which optimized by genetic algorithms. Case studies prove that the model has good predictive results, and its comprehensive judgment reaches 90%. With a certain degree of generalization ability, the proposed model can play a role in steel enterprise financial crisis early warning.
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