Research on the Application of GA Improved Neural Network in the Prediction of Financial Crisis

摘要

Aiming at the prediction of the financial distress of the company and taking the Chinese manufacturing listed companies as the research object, the abnormal financial situation is specially treated as the sign of the listed companies in financial distress. Genetic algorithm is used as the pre-device of the neural network model to optimize the initial value and threshold value of the network input, shorten the training time of the network, and improve the prediction efficiency of the network. The sample data are from real financial statements of listed companies, and 67 companies with normal and abnormal financial conditions are selected for empirical research. The original financial crisis early warning model and the financial crisis early warning model based on genetic algorithm are constructed. Empirical research shows that the prediction accuracy of the optimization model is higher than that of the traditional BP neural network model, which can improve the financial crisis early warning ability and analysis efficiency of listed companies from the perspective of technology.