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DC Field | Value | Language |
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dc.contributor.author | Suleimenova, D | - |
dc.contributor.author | Bell, D | - |
dc.contributor.author | Groen, D | - |
dc.date.accessioned | 2019-07-22T08:41:07Z | - |
dc.date.available | 2017-10-17 | - |
dc.date.available | 2019-07-22T08:41:07Z | - |
dc.date.issued | 2017-10-17 | - |
dc.identifier.citation | Suleimenova, D., Bell, D. & Groen, D. (2017) 'A generalized simulation development approach for predicting refugee destinations' Scientific Reports, 7, 13377, pp. 1-13. doi: 10.1038/s41598-017-13828-9. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/18793 | - |
dc.description.abstract | © 2017, The Author(s). In recent years, global forced displacement has reached record levels, with 22.5 million refugees worldwide. Forecasting refugee movements is important, as accurate predictions can help save refugee lives by allowing governments and NGOs to conduct a better informed allocation of humanitarian resources. Here, we propose a generalized simulation development approach to predict the destinations of refugee movements in conflict regions. In this approach, we synthesize data from UNHCR, ACLED and Bing Maps to construct agent-based simulations of refugee movements. We apply our approach to develop, run and validate refugee movement simulations set in three major African conflicts, estimating the distribution of incoming refugees across destination camps, given the expected total number of refugees in the conflict. Our simulations consistently predict more than 75% of the refugee destinations correctly after the first 12 days, and consistently outperform alternative naive forecasting techniques. Using our approach, we are also able to reproduce key trends in refugee arrival rates found in the UNHCR data. | en_US |
dc.format.extent | 1 - 13 (13) | - |
dc.language.iso | en | en_US |
dc.publisher | Nature Research | en_US |
dc.rights | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/. | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.title | A generalized simulation development approach for predicting refugee destinations | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1038/s41598-017-13828-9 | - |
dc.relation.isPartOf | Scientific Reports | - |
pubs.publication-status | Published | - |
pubs.volume | 7 | - |
dc.identifier.eissn | 2045-2322 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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