Measurement and Spatiotemporal Evolution of High-Quality Economic Development at the County Level Based on Machine Learning Methods: A Case Study of Guangdong Province

被引:0
|
作者
Liu, Shuhua [1 ]
Fang, Haijing [1 ]
机构
[1] Lingnan Normal Univ, Zhanjiang 524048, Guangdong, Peoples R China
关键词
Machine learning; county-level economy; high-quality development; spatiotemporal evolution; regional differences; innovation capacity;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This article develops a five-dimensional evaluation system for assessing high-quality economic development at the county level, employing the entropy method to analyze economic progress in 57 counties across Guangdong Province from 2010 to 2020.Utilizing machine learning techniques, the study uncovers the spatiotemporal dynamics and regional disparities in economic development at this level within Guangdong. Findings indicate a consistent annual improvement in the quality of economic development across the counties, with growing absolute disparities that display characteristics of "club convergence." Notably, the Pearl River Delta and the eastern and western parts of Guangdong exhibit a multipolar growth pattern, with regional variances primarily driving the overall disparities in high-quality economic development at the county level in Guangdong Province.
引用
收藏
页码:202 / 212
页数:11
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