一个开源和空间多样化的合成人口数据集,用于基于代理的建模和爱尔兰的微模拟
Seán Caulfield Curley1, Karl Mason1, Patrick Mannion1
1School of Computer Science, University of Galway, Galway, Ireland.
Data in brief
|June 9, 2025
概括
为准确的空间微模拟建模,生成对爱尔兰具有代表性的合成人口至关重要. 本研究评估了创建现实的合成个体的四种方法,确保数据隐私,同时捕捉基本的社会经济特征.
科学领域:
- 社会经济建模的社会经济建模.
- 计算社会科学 计算社会科学
- 人口综合研究
背景情况:
- 空间微模拟模型需要准确的个体级数据来实现现实的场景建模.
- 隐私问题在许多地区限制了对个人数据的访问,包括爱尔兰.
- 爱尔兰共和国需要一个代表性的合成种群.
研究的目的:
- 开发和评估四种不同的方法,以在爱尔兰共和国的选举部门层面产生合成人口.
- 确保合成人口准确地反映现实世界的社会经济特征.
- 为了应对数据隐私的挑战,同时实现微细的社会经济分析.
主要方法:
- 利用中央统计局 (CSO) 的劳动力调查进行现实的个人特征抽样.
- 雇佣的民间社会组织人口普查小区人口统计数据以实现空间异质性.
- 六个主要个体特征的匹配总计数:年龄组,性别,婚姻状况,房屋大小,主要经济状况和教育水平.
主要成果:
- 通过使用四种不同的方法,成功地在选举部门层面为爱尔兰共和国生成了合成种群.
- 通过结合调查和人口普查数据,证明了创造现实的合成个体的可行性.
- 通过匹配总人口特征来验证空间异质性.
结论:
- 提出的方法提供了一种可行的方法,用于在数据稀缺的环境中创建用于空间微模拟的代表性合成种群.
- 这项工作为爱尔兰提供了保护隐私,精细规模的社会经济建模.
- 生成的合成人口可以支持政策分析和场景规划.
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