Research on Forecasting the Development Trends of Digital Economy Based on Time Series Analysis

In response to the problem of single data and short time span in the research of predicting the development trend of the digital economy, a prediction method based on time series analysis is introduced to study the long-term evolution trend of the development of the digital economy. A time series analysis on the collected data is conducted to observe the presence of missing values, outliers, and non stationarity issues. The data based on the observed issues is preprocessed. After preprocessing the data, the parameter values of the ARIMA model by adjusting the parameter values of p, d, q are adjusted. Then the preprocessed parameters are imported into the adjusted ARIMA model and the predicted results are compared with the actual data. The results indicate that the ARIMA model can effectively predict the development trend of the digital economy. By using time series analysis methods, this study aims to investigate the long-term evolution trends of digital economy development, improve the accuracy and reliability of digital economy predictions, and provide more effective decision-making support for governments, enterprises, and individuals.