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Research on Prediction of the Digital Economy Index Based on Improved Sparrow Search Algorithm
Paper Type  |
Contributed Paper |
Title |
Research on Prediction of the Digital Economy Index Based on Improved Sparrow Search Algorithm |
Author |
Qing Hu and Fenhua Zhu |
Email |
Huqing@abc.edu.cn |
|
Abstract: The significant role of the digital economy in social development has been increasingly emphasized, and its development has become a national strategic priority. To improve the precision of forecasting the index for the digital economy, a novel model based on the improved sparrow search algorithm (ISSA) is proposed. The global search performance of the sparrow search algorithm (SSA) was used to optimize the parameters of the model to address the issues of convergence accuracy and speed of the model. Additionally, aiming at rectifying deficiencies in the optimization process of SSA, we introduced a variety of optimization strategies to augment both the global search capability and convergence ability of the algorithm, consequently further improving its predictive performance and constructing a new prediction model (ISSA-BP). Finally, we employed the ISSA-BP model to predict the digital economy index in the central and eastern regions of China. The experiment results demonstrate a notable improvement in the accuracy of prediction and the speed of convergence obtained by this model, while also providing a new research approach for forecasting in the digital economy. |
|
Article ID |
e2025017 |
Received Date |
2024-08-27 |
Revised Date |
2025-02-14 |
Accepted Date |
2025-02-24 |
Published Date |
2025-03-24 |
Full Text |
Download |
Keyword |
optimization strategy, machine learning, intelligent optimization algorithm, digital economy |
Volume |
Vol.52 No.2 (March 2025) |
DOI |
https://doi.org/10.12982/CMJS.2025.017 |
Citation |
Hu Q. and Zhu F., Research on Prediction of the Digital Economy Index Based on Improved Sparrow Search Algorithm, Chiang Mai Journal of Science, 2025; 52(2): e2025017. DOI 10.12982/CMJS.2025.017. |
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