LAUSR

The application of Internet of Things technology provides conditions for the systematization of enterprise financial data and the intellectualization of financial management. In this study, support vector machine (SVM) algorithm and genetic algorithm (GA) are combined to obtain the innovation model of enterprise financial information intelligent processing based on GA-SVM optimization algorithm. Nine factors affecting enterprise financial information processing from 2010 to 2018 are selected as influencing factors, and according to the idea and method of data modeling, the simulation experiment of enterprise financial information intelligent processing model is carried out with MATLAB. The results show that the average fitness of GA-SVM is close to the best fitness, indicating that each individual in the population is near the optimal solution. The RMSE of GA-SVM is 0.35%, and the root mean square error obtained is greater than this value, which shows that the application effect of GA-SVM is significantly better than that of SVM using cross validation method, and it is more suitable for precision prediction. At the same time, it also reflects that the optimization of SVM parameters by GA is reliable. The algorithm can be better applied in the intelligent processing of enterprise financial information and can provide a certain reference for enterprises in the financial management based on the Internet of Things.