Population Synthesis Based on Joint Distribution Inference Without Disaggregate Samples | |
Ye, Peijun1,2; Hu, Xiaolin3; Yuan, Yong1,2; Wang, Fei-Yue1,2,4 | |
发表期刊 | JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION |
2017-10-31 | |
卷号 | 20期号:4页码:16 |
文章类型 | Article |
摘要 | Synthetic population is a fundamental input to dynamic micro-simulation in social applications. Based on the review of current major approaches, this paper presents a new sample-free synthesis method by inferring joint distribution of the total target population. Convergence of multivariate Iterative Proportional Fitting used in our method is also proved theoretically. The method, together with other major ones, is applied to generate a nationwide synthetic population database of China by using its overall cross-classification tables as well as a sample from census. Marginal and partial joint distribution consistencies of each database are compared and evaluated quantitatively. Final results manifest sample-based methods have better performances on marginal indicators while the sample-free ones match partial distributions more precisely. Among the five methods, our proposed method can significantly reduce the computational cost for generating synthetic population in large scale. An open source implementation of the population synthesizer based on C# used in this research is available at https://github.com/PeijunYe/PopulationSynthesis.git. |
关键词 | Population Synthesis Sample-free Iterative Proportional Fitting |
WOS标题词 | Social Sciences |
DOI | 10.18564/jasss.3533 |
关键词[WOS] | PROPORTIONAL FITTING PROCEDURE ; CONTINGENCY-TABLES ; GENERATION ; MICROSIMULATION ; CONVERGENCE ; SIMBRITAIN ; MATRICES ; MARGINS |
收录类别 | SSCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(61603381 ; Department of Energy, USA(4000152851) ; 71472174 ; 61533019 ; 71232006) |
WOS研究方向 | Social Sciences - Other Topics |
WOS类目 | Social Sciences, Interdisciplinary |
WOS记录号 | WOS:000416164100018 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/20084 |
专题 | 复杂系统管理与控制国家重点实验室_平行智能技术与系统团队 |
作者单位 | 1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Qingdao Acad Intelligent Ind, Qingdao, Peoples R China 3.Georgia State Univ, Dept Comp Sci, 25 Pk Pl, Atlanta, GA 30084 USA 4.Natl Univ Def & Technol, Mil Computat Expt & Parallel Syst Res Ctr, Changsha, Hunan, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ye, Peijun,Hu, Xiaolin,Yuan, Yong,et al. Population Synthesis Based on Joint Distribution Inference Without Disaggregate Samples[J]. JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION,2017,20(4):16. |
APA | Ye, Peijun,Hu, Xiaolin,Yuan, Yong,&Wang, Fei-Yue.(2017).Population Synthesis Based on Joint Distribution Inference Without Disaggregate Samples.JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION,20(4),16. |
MLA | Ye, Peijun,et al."Population Synthesis Based on Joint Distribution Inference Without Disaggregate Samples".JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION 20.4(2017):16. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Population Synthesis(1326KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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