Synthesizing Large-scale Household Composition Considering Family Type and Role in Household
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- HARADA Takuya
- Graduate School of Informatics, Kansai University
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- MURATA Tadahiko
- Faculty of Informatics, Kansai University
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- MASUI Daiki
- Graduate School of Informatics, Kansai University
Bibliographic Information
- Other Title
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- 家族類型と世帯内の役割を考慮したSA法による大規模世帯の合成
- カゾク ルイケイ ト セタイ ナイ ノ ヤクワリ オ コウリョ シタ SAホウ ニ ヨル ダイキボ セタイ ノ ゴウセイ
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Abstract
<p>In this paper, we modify a simulated annealing-based (SA-based) household synthesizing method in order to synthesize a population in the same scale of the target area. Micro-simulations (MS) and agent-based simulations (ABS) are recently employed for social simulations. For enabling MS or ABS, each household composition such as ages, occupations, or other properties of each member of a household should be prepared before simulations. However real household compositions are not available to researchers due to privacy or security reasons. Therefore, we need to synthesize household compositions from available statistics for MS or ABS. However, it should be noted that the synthesized population is just an artificial population that is suitable to the employed statistics. In this paper, we modify an SA-based household synthesizing method based on statistics. We propose a household generation method, new 21 statistics, and an age exchange method for members in households. In our previous research, we employed nine statistics to synthesize populations. In this paper, we synthesize an artificial population from 21 statistics, and we show how errors between the artificial population and real statistics are reduced by the proposed algorithm.</p>
Journal
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- Transactions of the Society of Instrument and Control Engineers
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Transactions of the Society of Instrument and Control Engineers 54 (9), 705-717, 2018
The Society of Instrument and Control Engineers
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Keywords
Details 詳細情報について
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- CRID
- 1390282763047635840
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- NII Article ID
- 130007485455
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- NII Book ID
- AN00072392
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- ISSN
- 18838189
- 04534654
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- NDL BIB ID
- 029263482
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed