Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

September 3, 2024


Pages


DOI

Article

Mutual Influence Mechanism and Optimization Strategy of University Town and Urban Economic Growth Based on Time Series Forecasting Model

Check for updates


Authors

Yihuo Jiang Affiliation:
Xiamen Institute of Technology, Xiamen, Fujian, 361021, China.
and Fuji Lan Affiliation:
Xiamen Institute of Technology, Xiamen, Fujian, 361021, China.


Abstract

University towns and urban economic growth have important interactions, and time series forecasting models can enable urban planners to better clarify the relationship between the two so as to make more scientific and reasonable decisions. Based on the time series forecasting model constructed in this paper, this paper analyzes and forecasts the relationship between university cities and urban economic growth in C. The main conclusions of this paper are that the p-value of ARIMA(0,2,3) and ARIMA(1,1,1) models is lower than 0.05, and the prediction accuracy of ARIMA(1,1,1) model is higher than that of ARIMA(0,2,3) and ARIMA(1,1,1) model in the prediction of the two. ARIMA(0,2,3) with predicted values of 27631.3, 31541.5, and 24412.45, and the error values from the actual values are only 304.98, 1997.49, and 867.95. This paper’s time series prediction model has achieved good results, as evidenced by this. Y1 shows a highly positive correlation with X1, X3, and X4 and a significant positive correlation with X2, which leads to the conclusion that the total amount of investment in urban construction of the university city of C city has a substantial relationship with the economic growth of C city.


Keywords

Time series analysis, ARIMAX model, Forecasting model, University town, Urban economy, 91B52


Citation

Jiang, Y. & Lan, F. (2024). Mutual influence mechanism and optimization strategy of university town and urban economic growth based on time series forecasting model. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-2264
0 Total citations
0.00 FWCI
0 Recent citations
(2 years)
14 References
Open Access Yes
View full metrics

Published by: Engineering Journals

Engineering Journals Logo