Multilevel Modeling as a Methodology for the Simulation of Human Mobility Article Swipe
Luca Serena
,
Moreno Marzolla
,
Gabriele D’Angelo
,
Stefano Ferretti
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/ds-rt55542.2022.9932080
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/ds-rt55542.2022.9932080
Multilevel modeling is increasingly relevant in the context of modelling and simulation since it leads to several potential benefits, such as software reuse and integration, the split of semantically separated levels into sub-models, the possibility to employ different levels of detail, and the potential for parallel execution. The coupling that inevitably exists between the sub-models, however, implies the need for maintaining consistency between the various components, more so when different simulation paradigms are employed (e.g., sequential vs parallel, discrete vs continuous). In this paper we argue that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the “micro” and “macro” layer, where individual entities (micro) and long-range interactions (macro) are described. In this paper we investigate the challenges of multilevel modeling, and describe some preliminary results using prototype implementations of multilayer simulators in the context of epidemic diffusion and vehicle pollution.
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- https://doi.org/10.1109/ds-rt55542.2022.9932080
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https://doi.org/10.1109/ds-rt55542.2022.9932080Digital Object Identifier
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Multilevel Modeling as a Methodology for the Simulation of Human MobilityWork title
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preprintOpenAlex work type
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enPrimary language
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2022Year of publication
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2022-09-26Full publication date if available
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Luca Serena, Moreno Marzolla, Gabriele D’Angelo, Stefano FerrettiList of authors in order
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https://doi.org/10.1109/ds-rt55542.2022.9932080Publisher landing page
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greenOpen access status per OpenAlex
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Computer scienceTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2024: 1, 2023: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.components, | 65 |
| abstract_inverted_index.consistency | 61 |
| abstract_inverted_index.investigate | 130 |
| abstract_inverted_index.maintaining | 60 |
| abstract_inverted_index.possibility | 34 |
| abstract_inverted_index.preliminary | 139 |
| abstract_inverted_index.sub-models, | 32, 54 |
| abstract_inverted_index.“macro” | 114 |
| abstract_inverted_index.“micro” | 112 |
| abstract_inverted_index.continuous). | 80 |
| abstract_inverted_index.increasingly | 3 |
| abstract_inverted_index.integration, | 24 |
| abstract_inverted_index.interactions | 122 |
| abstract_inverted_index.semantically | 28 |
| abstract_inverted_index.decomposition | 104 |
| abstract_inverted_index.implementations | 143 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.7900000214576721 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.76090676 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |