The Application of Artificial Neural Networks in Macroeconomic Forecasting

In macroeconomic forecasting, applied research is very important to predict the accuracy of games, but there is a problem of misoperation and positioning. Conventional deep learning algorithms cannot effectively solve the applied research problems in macroeconomic forecasting, and the results are not ideal. Therefore, an applied research method based on artificial neural network is proposed and its application in macroeconomic forecasting is evaluated. First, influencing factors were identified using alternating neural theory and indicators were classified as needed to reduce interfering factors. Then, an application research scheme of artificial neural network is constructed by using alternating neural theory, and the results are analyzed in detail. The MATLAB simulation results show that under some specific evaluation conditions, the artificial neural network is superior to the standard deep learning algorithm in the accuracy of applied research and the time of influencing factors.