Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An Integrated Framework for Population Synthesis at Fine-Grained Spatial Scales
https://orcid.org/http://orcid.org/0000-0002-6807-874X
https://orcid.org/http://orcid.org/0000-0001-5172-9967
https://orcid.org/http://orcid.org/0000-0003-3388-6197
https://orcid.org/http://orcid.org/0000-0002-9927-3724
https://orcid.org/http://orcid.org/0000-0001-6287-8095
With the conception and development of Smart City and its applications, Digital Twins and other related technologies have been growing rapidly during the past years. Simultaneously, in the fields of transportation and urban analytics, agent-based models (ABMs) and microsimulations have also gained popularity, partly echoing the Digital Twins initiatives in Smart City applications, and is also owing to the sharply rising utilizability of high-performance computation resources and rapidly boosting high scale data storage. This study mainly developed a population synthesis pipeline to generate spatially detailed populations in urban environments and combined probabilistic models and re-weighting techniques for agent synthesis to cope with microdata on heterogeneity and marginal control matching. We also structured the built environment with higher spatial resolution than previous studies. We then created a realistic and spatially fine-grained synthetic population by the assignment of agents to the spatial units via rule-based and behavioral modeling. The results show good performance in terms of the accuracies over different dimensions and the proposed pipeline can facilitate the use of ABMs in Smart City projects.
An Integrated Framework for Population Synthesis at Fine-Grained Spatial Scales
https://orcid.org/http://orcid.org/0000-0002-6807-874X
https://orcid.org/http://orcid.org/0000-0001-5172-9967
https://orcid.org/http://orcid.org/0000-0003-3388-6197
https://orcid.org/http://orcid.org/0000-0002-9927-3724
https://orcid.org/http://orcid.org/0000-0001-6287-8095
With the conception and development of Smart City and its applications, Digital Twins and other related technologies have been growing rapidly during the past years. Simultaneously, in the fields of transportation and urban analytics, agent-based models (ABMs) and microsimulations have also gained popularity, partly echoing the Digital Twins initiatives in Smart City applications, and is also owing to the sharply rising utilizability of high-performance computation resources and rapidly boosting high scale data storage. This study mainly developed a population synthesis pipeline to generate spatially detailed populations in urban environments and combined probabilistic models and re-weighting techniques for agent synthesis to cope with microdata on heterogeneity and marginal control matching. We also structured the built environment with higher spatial resolution than previous studies. We then created a realistic and spatially fine-grained synthetic population by the assignment of agents to the spatial units via rule-based and behavioral modeling. The results show good performance in terms of the accuracies over different dimensions and the proposed pipeline can facilitate the use of ABMs in Smart City projects.
An Integrated Framework for Population Synthesis at Fine-Grained Spatial Scales
https://orcid.org/http://orcid.org/0000-0002-6807-874X
https://orcid.org/http://orcid.org/0000-0001-5172-9967
https://orcid.org/http://orcid.org/0000-0003-3388-6197
https://orcid.org/http://orcid.org/0000-0002-9927-3724
https://orcid.org/http://orcid.org/0000-0001-6287-8095
With the conception and development of Smart City and its applications, Digital Twins and other related technologies have been growing rapidly during the past years. Simultaneously, in the fields of transportation and urban analytics, agent-based models (ABMs) and microsimulations have also gained popularity, partly echoing the Digital Twins initiatives in Smart City applications, and is also owing to the sharply rising utilizability of high-performance computation resources and rapidly boosting high scale data storage. This study mainly developed a population synthesis pipeline to generate spatially detailed populations in urban environments and combined probabilistic models and re-weighting techniques for agent synthesis to cope with microdata on heterogeneity and marginal control matching. We also structured the built environment with higher spatial resolution than previous studies. We then created a realistic and spatially fine-grained synthetic population by the assignment of agents to the spatial units via rule-based and behavioral modeling. The results show good performance in terms of the accuracies over different dimensions and the proposed pipeline can facilitate the use of ABMs in Smart City projects.
An Integrated Framework for Population Synthesis at Fine-Grained Spatial Scales
Lecture Notes in Civil Engineering
Guo, Wei (Herausgeber:in) / Qian, Kai (Herausgeber:in) / Huang, Yinni (Autor:in) / Zhou, Meng (Autor:in) / Deng, Runqin (Autor:in) / Huang, Zeteng (Autor:in) / You, Linlin (Autor:in)
International Conference on Green Building, Civil Engineering and Smart City ; 2022 ; Guilin, China
Proceedings of the 2022 International Conference on Green Building, Civil Engineering and Smart City ; Kapitel: 129 ; 1255-1262
08.09.2022
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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