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一个用于爱尔兰基于智能体建模和微观模拟的开源且空间多样的合成人口数据集。

An open-source and spatially diverse synthetic population dataset for agent-based modelling and microsimulation in Ireland.

作者信息

Caulfield Curley Seán, Mason Karl, Mannion Patrick

机构信息

School of Computer Science, University of Galway, Galway, Ireland.

出版信息

Data Brief. 2025 May 1;60:111611. doi: 10.1016/j.dib.2025.111611. eCollection 2025 Jun.

Abstract

Spatial microsimulations, where simulation units represent people or households in a small area, are extremely useful for modelling a wide range of socio-economic scenarios at a fine scale. The characteristics of individuals in these simulations' populations need to accurately represent the real characteristics of the target area to model realistic scenarios. However, individual-level data is not available for the vast majority of populations, Ireland included, due to privacy concerns. Thus, a representative synthetic population for the Republic of Ireland is needed. The data from four methods of generating synthetic populations at the Electoral Division level are given in this paper. Realistic individuals are created by sampling from the Central Statistics Office (CSO) Labour Force Survey. Spatial heterogeneity is achieved by matching the aggregate counts of individuals' characteristics to those from the CSO Census Small Area Population Statistics. Individuals are assigned six characteristics: age group, sex, marital status, house size, primary economic status, and highest level of education achieved.

摘要

空间微观模拟中,模拟单元代表小区域内的个人或家庭,对于在精细尺度上模拟广泛的社会经济情景极为有用。这些模拟人口中个体的特征需要准确反映目标区域的真实特征,以便模拟现实情景。然而,由于隐私问题,绝大多数人口(包括爱尔兰)都没有个体层面的数据。因此,需要为爱尔兰共和国创建一个具有代表性的合成人口。本文给出了在选区层面生成合成人口的四种方法的数据。通过从中央统计局(CSO)劳动力调查中抽样来创建现实的个体。通过将个体特征的总计与CSO人口普查小区域人口统计数据中的总计相匹配来实现空间异质性。个体被赋予六个特征:年龄组、性别、婚姻状况、房屋大小、主要经济状况以及所达到的最高教育水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/094c/12145541/703a210bf8bc/ga1.jpg

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