基于随机森林算法对中国人口-生态-能源-数字经济的合协调的主要因素的研究
Qikang Zhong1, Jiawei Zhu2, Zhe Li1
1School of Architecture and Art, Central South University, Changsha, 410083, China.
Scientific reports
|May 20, 2025
概括
中国中国中国中国.
科学领域:
- 环境科学 环境科学
- 区域经济学 区域经济学
- 可持续发展研究 可持续发展研究
背景情况:
- 中国的快速发展为平衡人口,生态,能源和数字经济 (PEED) 系统带来了复杂的挑战.
- 了解这些系统的合协调发展 (CCD) 对可持续的区域增长至关重要.
- 中国的发展存在显著的区域差异,需要有针对性的战略.
研究的目的:
- 在中国 (2011-2020年) 分析PEED系统CCD的时空模式.
- 确定影响PEED系统CCD的主导因素.
- 为均衡和可持续的区域发展提供政策建议.
主要方法:
- 使用来自中国31个省份的面板数据构建了一个PEED协调指数.
- 应用了合协调模型,空间自相关性 (莫兰的I) 和地质探测器模型.
- 利用随机森林和SHAP分析来确定关键驱动因素及其影响.
主要成果:
- 总体而言,中国的PEED系统CCD显示稳步改善,但仍然存在显著的区域差异.
- 东部省份在协调方面处于领先地位,而西部和东北部地区则落后.
- 生态子系统的空间差异很大;数字经济子系统更为均.
- 夜间光线指数,城市化率和绿色覆盖率是关键驱动因素,夜间光线指数是最具影响力的.
结论:
- PEED系统的CCD正在改善,但在中国分布不均.
- 需要在城市规划,生态保护,能源和数字基础设施方面进行有针对性的干预,特别是在落后的地区.
- 调查结果支持制定政策,以实现可持续发展目标 (SDGs).
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