综合人口数据库:基于agent模型的美国地理空间数据库。

William D Wheaton, James C Cajka, Bernadette M Chasteen, Diane K Wagener, Philip C Cooley, Laxminarayana Ganapathi, Douglas J Roberts, Justine L Allpress
{"title":"综合人口数据库:基于agent模型的美国地理空间数据库。","authors":"William D Wheaton,&nbsp;James C Cajka,&nbsp;Bernadette M Chasteen,&nbsp;Diane K Wagener,&nbsp;Philip C Cooley,&nbsp;Laxminarayana Ganapathi,&nbsp;Douglas J Roberts,&nbsp;Justine L Allpress","doi":"10.3768/rtipress.2009.mr.0010.0905","DOIUrl":null,"url":null,"abstract":"<p><p>Agent-based models simulate large-scale social systems. They assign behaviors and activities to \"agents\" (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses.RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants.For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models.Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.</p>","PeriodicalId":88935,"journal":{"name":"Methods report (RTI Press)","volume":"2009 10","pages":"905"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875687/pdf/nihms-142155.pdf","citationCount":"128","resultStr":"{\"title\":\"Synthesized Population Databases: A US Geospatial Database for Agent-Based Models.\",\"authors\":\"William D Wheaton,&nbsp;James C Cajka,&nbsp;Bernadette M Chasteen,&nbsp;Diane K Wagener,&nbsp;Philip C Cooley,&nbsp;Laxminarayana Ganapathi,&nbsp;Douglas J Roberts,&nbsp;Justine L Allpress\",\"doi\":\"10.3768/rtipress.2009.mr.0010.0905\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Agent-based models simulate large-scale social systems. They assign behaviors and activities to \\\"agents\\\" (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses.RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants.For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models.Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.</p>\",\"PeriodicalId\":88935,\"journal\":{\"name\":\"Methods report (RTI Press)\",\"volume\":\"2009 10\",\"pages\":\"905\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875687/pdf/nihms-142155.pdf\",\"citationCount\":\"128\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Methods report (RTI Press)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3768/rtipress.2009.mr.0010.0905\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methods report (RTI Press)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3768/rtipress.2009.mr.0010.0905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 128

摘要

基于主体的模型模拟大规模的社会系统。他们将行为和活动分配给被建模群体中的“代理”(个体),然后允许代理在复杂的模拟中与环境和彼此交互。除其他用途外,基于主体的模型经常用于模拟传染病暴发。RTI使用并扩展了一种迭代比例拟合方法,生成了一个综合的、地理空间明确的人类代理数据库,该数据库代表了2000年美国50个州和哥伦比亚特区的人口。每个代理人被分配到一个家庭;其他代理人构成住户。对于这个数据库,RTI开发了生成合成家庭和个人的方法,将代理人分配到学校和工作场所,以便在代理人进行日常活动时可以考虑他们之间的复杂交互,生成占据群体宿舍(军事基地,大学宿舍,监狱,养老院)的合成人类代理人。在本报告中,我们描述了用于生成综合人口数据库的方法以及数据库的最终数据结构和数据内容。这些信息将为研究人员提供在开发基于代理的模型时使用该数据库所需的信息。任何用户都可以根据请求使用合成代理数据库的部分内容。RTI将为希望在自己的基于代理的模型中使用该数据库的用户提取数据库的一部分(县、地区或州)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Synthesized Population Databases: A US Geospatial Database for Agent-Based Models.

Agent-based models simulate large-scale social systems. They assign behaviors and activities to "agents" (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses.RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants.For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models.Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Visual Attention to Tobacco-Related Stimuli in a 3D Virtual Store Interactive visualization to facilitate monitoring longitudinal survey data and paradata Implications of Alternative Land Conversion Cost Specifications on Projected Afforestation Potential in the United States. A Control Theory Model of Smoking. Visualization of Categorical Longitudinal and Times Series Data.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1