BP神经网络模型在湖北省GDP预测中的应用——与时间序列模型的对比分析

The Application of BP Neural Network Model in the GDP Forecast of Hubei Province——Compared with Time Series Model

本文探讨了神经网络模型及其优化算法在宏观经济预测中的应用,通过寻找最佳参数,建立BP网络预测模型对湖北省GDP进行了预测分析。同时还与传统时间序列模型作了对比研究,实证结果表明,神经网络预测精度明显优于时间序列模型。

This paper discusses the application of neural network model and the optimization algorithms in prediction of macroeconomic and predicts the GDP of Hubei province by searching optimal parameters and establishing BP network forecast model.By comparison with traditional time series model,the empirical results show that the prediction accuracy of neural network is obviously superior to the time series model.