Integrating Bayesian network and generalized raking for population synthesis in Greater Jakarta. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Ilahi, Anugrah; Axhausen, Kay W.
• Is Part Of: Regional studies, regional science. Volume 6:Issue 1(2019)
• Page Start: 623
• Page End: 636
• Publication Date: 2019-01-01
• Subjects: Bayesian network -- generalized raking -- population synthesis -- agent-based model; Regional planning -- Periodicals; Regional economics -- Periodicals; Regional economics; Regional planning; Periodicals; 300
• DOI: 10.1080/21681376.2019.1687011
• Languages: English
• ISSNs: 2168-1376

Abstract

ABSTRACT: 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.