Research on Financial Risk Evaluation and Control of Tourism Enterprises Based on Improved GA Algorithm

Abstract

AbstractWith the change and complexity of the tourism market environment, the financial risks faced by tourism enterprises are increasingly diversified. Effectively evaluating and controlling these financial risks has become the key to the development of tourism enterprises. Therefore, this study builds an accurate and real-time enterprise financial risk assessment and control model with the help of genetic algorithm. The results show that compared with other models, the maximum error value of the research model is only 0.12, and the maximum mean square error is only 0.09. The high reliability of the model is verified by simulating the data of selected tourism enterprises. After increasing the number of samples, the accuracy of the model continues to improve, and the predicted financial indicators are more in line with the actual situation. The model achieves the best results in average fitness, and the required error value is reached within 10 iterations. In the goodness of fit comparison, the goodness of fit of the training set, the test set and the verification set of the model are all over 0.7. In the empirical analysis, the ACC of the research model reached 97.4%, the accuracy rate reached 97.1%, the F1 index of the research reached 98.6%, and the other three research models were all lower than 98%. The above shows that the research model has significant advantages and can effectively evaluate and control the financial risk of tourism enterprises.