Research on Macroeconomic Prediction Technology Based on Wavelet Neural Network

The trend of future macroeconomic changes presented by countries and regions is real time, and will be affected by a variety of factors during the practical operation. In previous research projects, the forecasting methods proposed for the macro-economy could not scientifically deal with the problems such as the inability to accurately evaluate the nonlinear system. Therefore, researchers proposed a macroeconomic forecasting technology based on the optimization of wavelet neural networks in practice and exploration. Different from the current BP neural network prediction model, the wavelet neural network is used to carry out prediction analysis, and the weight proposed by the model is studied by combining with the intelligent swarm algorithm, and then it is optimized. At the same time, combining with the economic data of a certain province has been normalized, the training analysis is carried out on the research model proposed in this paper. According to the final results, the wavelet neural network is more accurate than the BP neural network in predicting results.