Prediction of China's Digital Economy Scales based on ARIMA and BP Neural Network

The scale of the digital economy is an important quantitative index to measure the development level of a country's digital economy. Through reasonable and scientific prediction of the scale of China's digital economy, it can not only further understand the development situation of the digital economy objectively and fairly, but also provide a reference for the government to conduct macro-control of the digital economy based on the existing data. Based on the ARIMA model and BP neural network, this paper constructs a variety of prediction models for the size of China's digital economy and makes an empirical analysis of the effectiveness of the models through the size data of China's digital economy from 1993 to 2020. The results show that the combination model constructed by using the error correction strategy has the better fitting and prediction effect, the performance of MAPE, MAE,
$R^{2}$
, and other evaluation indicators is better than that of the single model, and the combined model based on the weight allocation method.