Economic Forecast Model and Development Path Analysis Based on BP and RBF Neural Network

Economic Forecast Model and Development Path Analysis Based on BP and RBF Neural Network

연구 분야: Artificial Intelligence

학회: 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT)

In recent years, the economy of Guangdong province has ranked first in China for many consecutive years, with a strong growth momentum. In the future, whether Guangdong’s GDP can maintain high-quality growth is an important issue. Neural network is an important tool for prediction. The neural network is mainly divided into BP neural network and RBF neural network. Combining the economic forecasting theory and the characteristics of BP neural network algorithm and RBF neural network, this paper studies the economic growth prediction of Guangdong province based on the artificial neural network algorithm and RBF neural network algorithm. The results of empirical research show that the artificial neural network has good prediction accuracy, but the data of economic growth prediction by various neural networks are different, and some errors are very large. Compared with BP neural network, RBF neural network model is one of good economic prediction models with high accuracy and less time.