WEKO3
アイテム
Workplace Assignment to Workers in Synthetic Populations in Japan
http://hdl.handle.net/10112/00028288
http://hdl.handle.net/10112/000282883db76efb-dcaf-4934-baa1-94421431bd69
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
KU-1100-20221107-01.pdf (5.3 MB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||
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| 公開日 | 2023-04-24 | |||||||||
| タイトル | ||||||||||
| タイトル | Workplace Assignment to Workers in Synthetic Populations in Japan | |||||||||
| 言語 | en | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者 |
村田, 忠彦
× 村田, 忠彦
WEKO
5533
× 岩瀬, 大樹× 原田, 拓弥 |
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| 概要 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | 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. | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant 20K10362 | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Kansai University Fund for Supporting Outlay Research Centers, 2020–2021 | |||||||||
| 書誌情報 |
IEEE Transactions on Computational Social Systems p. 1-10, 発行日 2022-11-07 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | PISSN | |||||||||
| 収録物識別子 | 2329924X | |||||||||
| DOI | ||||||||||
| 関連タイプ | isIdenticalTo | |||||||||
| 識別子タイプ | DOI | |||||||||
| 関連識別子 | 10.1109/TCSS.2022.3217614 | |||||||||
| 著者版フラグ | ||||||||||
| 出版タイプ | VoR | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||
| 出版者 | ||||||||||
| 出版者 | IEEE | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Agent-based modeling | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | daytime population distribution | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | microsimulations | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | social simulations | |||||||||
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| 主題Scheme | Other | |||||||||
| 主題 | synthetic population | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | workplace assignment | |||||||||
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| 主題Scheme | Other | |||||||||
| 主題 | 合成人口データ | |||||||||
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| 主題Scheme | Other | |||||||||
| 主題 | 社会シミュレーション | |||||||||
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| 主題Scheme | Other | |||||||||
| 主題 | 昼間人口 | |||||||||
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| 主題Scheme | Other | |||||||||
| 主題 | 関西大学 | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | Kansai University | |||||||||
