文章基本信息

标题：Integrating Bayesian network and generalized raking for population synthesis in Greater Jakarta
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作者：Anugrah Ilahi ; Kay W. Axhausen
期刊名称：Regional Studies, Regional Science
印刷版ISSN：2168-1376
电子版ISSN：2168-1376
出版年度：2019
卷号：6
期号：1
页码：1-15
DOI：10.1080/21681376.2019.1687011
出版社：Taylor and Francis Ltd
摘要：Constructing agent data with detailed information on their sociodemographics is substantially important for agent-based modelling. However, to collect data about the whole population is not efficient, since it requires an expensive and time-consuming survey, especially for a large population. The paper uses a novel approach that integrates Bayesian network (BN) and generalized raking (GR) multilevel iterative proportional fitting (IPF). Furthermore, the approach is applied to construct the population for Greater Jakarta, Indonesia, which consists of 30 million inhabitants. The results show that the BN approach can produce data that represent the probability distribution of sample data and that the IPF can match it against aggregate census data.
关键词：Bayesian network ; generalized raking ; population synthesis ; agent-based model