Workplace Assignment to Workers in Synthetic Populations in Japan
Workplace Assignment to Workers in Synthetic Populations in Japan
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DOI：
10.1109/tcss.2022.3217614
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发表时间：
2022-11-07
影响因子：
5
通讯作者：
Harada，Takuya
中科院分区：
文献类型：
--
作者：
Murata，Tadahiko;Iwase，Daiki;Harada，Takuya
在本文中，我们使用在日本进行的多次人口普查，在合成人口中为每个家庭的每个工人分配工作场所属性。合成人口是根据人口普查数据合成的每个居民的一组人工个体属性。我们合成了一组日本的合成种群。我们为每个工人分配一个工作场所属性，以估计白天的人口分布，并在基于代理的或微观模拟中开发基于活动的模型。虽然政府发布了住宅区或工作场所的统计信息，并且手机公司发布了一些个人移动数据，但是很难收集工人的家庭和工作场所位置的信息以及他们的家庭和工作信息。我们采用来源地-目的地-行业（ODI）统计数据来估计工人的工作场所。由于ODI统计数据中的某些属性由于隐私原因而不可用，因此我们提出了一种工作场所分配方法，适用于日本所有使用限制ODI和OD统计数据的城市，城镇和村庄。我们展示了使用完整ODI统计数据的工人数量与建议的工作场所分配方法的工人数量之间的差异。我们表明，88.2%的工人在日本的一个城市被分配到正确的城市作为工作场所，我们提出的方法。我们还显示了几个地图的白天人口分布，我们提出的方法。具有工作场所属性的合成人口使真实规模的社会模拟能够在和平时期设计交通或商业系统，或者在紧急情况下（如灾害或流行病）估计受害者并计划恢复。
In this article, we assign workplace attributes to each worker in each household in a synthetic population using multiple censuses conducted in Japan. The synthetic population is a set of artificial individual attributes for each resident that is synthesized according to census data. We have synthesized a set of the synthetic populations of Japan. We assign a workplace attribute to each worker to estimate daytime population distribution and develop activity-based models in agent-based or microsimulations. Although statistical information in a residential area or a working place is released by the government and some individual moving data are released by cellphone companies, it is hard to collect the information with home and workplace location of a worker with their family and working information. We employ origin–destination–industry (ODI) statistics to estimate workplaces for workers. Since some attributes in ODI statistics are not available for privacy reasons, we propose a workplace assignment method for all cities, towns, and villages using restricted ODI and OD statistics in Japan. We show how much difference there are between the number of workers using the complete ODI statistics and the number of workers by the proposed workplace assignment method. We show that 88.2% of workers in a city in Japan are assigned to correct cities as workplaces by our proposed method. We also show several maps of daytime population distributions by our proposed method. Synthetic populations with workplace attributes enable real-scale social simulations to design transport or business systems in times of peace or to estimate victims and plan recoveries in times of emergency, such as disasters or pandemics.