Economic Trend Forecast Analysis Based On Time Series Algorithm
Sirong Mou · Procedia Computer Science · 2025
With the increasingly complex economic environment, it is particularly important to predict the economic situation accurately. Taking Dalian City as the specific research object, a large number of economy-related data were collected and pre-processed, and the economic development trend prediction model of Dalian City was built through time series analysis technology to analyze the influence of different factors on economic development. The triple exponential smoothing method, ARIMA model, linear regression and gray prediction algorithm were used for comparison. Experimental results show that triple exponential smoothing algorithm has the best performance when the coefficient of determination is 0.985, followed by ARIMA algorithm, linear regression and grey prediction algorithm have relatively weak performance, MSE 0.0035 and 0.004 respectively. The research results show that the algorithm can accurately capture the situation and fluctuation characteristics of Dalian’s economic development, help to understand the dynamic change law of Dalian’s economy, and provide decision support for government decision-making and enterprise planning, so as to better cope with the challenges and opportunities in economic development.