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Updated: Jun 24, 2025

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将现有的气候变化缓解政策数据集与混合机器学习方法进行协调
Libo Wu1,2,3,4, Zhihao Huang5, Xing Zhang5
1School of Data Science, Fudan University, Shanghai, 200433, China. wulibo@fudan.edu.cn.
Scientific data
|June 4, 2024
概括
一个新的全球气候变化缓解政策数据集 (GCCMPD) 提供了关于73,625个气候政策的全面数据. 此资源有助于了解各部门和实体的全球气候行动.
科学领域:
- 环境科学 环境科学
- 气候政策分析 气候政策分析
- 数据科学数据科学数据科学
背景情况:
- 全球气候政策的数量和范围越来越多,需要全面的数据.
- 现有的数据集缺乏关于政策要素和实施背景的多指标信息.
- 对全球一级数据集的需求,以跟踪气候变化缓解努力.
研究的目的:
- 开发全球气候变化缓解政策数据集 (GCCMPD).
- 提供关于气候政策及其实施的多指标数据集.
- 促进对全球气候活动的更深入理解.
主要方法:
- 使用了一种半监督混合机器学习方法.
- 综合政策信息来自全球,区域和特定部门的来源.
- 雇佣专家基于知识的字典映射,概率统计和自然语言处理.
主要成果:
- 开发了GCCMPD,其中包含来自216个实体的73,625条政策.
- 分类多个指标,包括目标,目标部门,工具和法律胁迫.
- 与政府间气候变化专门委员会 (IPCC) 排放部门分类相一致的数据集.
结论:
- GCCMPD提供有关气候减缓政策的详细和一致信息.
- 该数据集有助于政策制定者,研究人员和组织分析气候行动.
- 简化了跨国家,部门和实体的气候活动的比较.
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