Long-Term Forecast of Regional Economy Based on Least Squares Support Vector Machine

Litao Fan

2022

Abstract

Regional economic growth is a demand-led change. By reasonably forecasting and studying the patterns and operating mechanisms of economic growth changes in a specific range of regions, we will promote the sustainable growth of regional economy and society. In order to address the shortcomings of the existing research on regional economic forecasting in the medium and Long-Term, this paper briefly discusses the index system and sample data of the forecasting model proposed in this paper based on the least squares support vector machine (LLSSVM) and regional economic forecasting methods. The design of the forecasting model is also discussed, and the results of the least squares support vector machine for medium- and Long-Term regional economic forecasting are finally analyzed experimentally. The experimental data show that the error between the prediction results of least squares support vector for a city's economic GDP and the actual results is small, and its accuracy rate for a city's economic GDP prediction is about 96.5% on average, which is significantly better than the other two prediction models. Therefore, it is verified that the game model simulation based on ant colony algorithm performs better.

Paper Citation

in Harvard Style

Fan L. (2022). Long-Term Forecast of Regional Economy Based on Least Squares Support Vector Machine. In Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME; ISBN 978-989-758-636-1, SciTePress, pages 542-547. DOI: 10.5220/0012036500003620

in Bibtex Style

@conference{icemme22,
author={Litao Fan},
title={Long-Term Forecast of Regional Economy Based on Least Squares Support Vector Machine},
booktitle={Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME},
year={2022},
pages={542-547},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012036500003620},
isbn={978-989-758-636-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Economic Management and Model Engineering - Volume 1: ICEMME
TI - Long-Term Forecast of Regional Economy Based on Least Squares Support Vector Machine
SN - 978-989-758-636-1
AU - Fan L.
PY - 2022
SP - 542
EP - 547
DO - 10.5220/0012036500003620
PB - SciTePress