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The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy
Many practical networks, such as city networks, road networks and neural networks, usually grow up on basis of topological structures and geographical measures. Big hubs, importance of which have been well known in complex networks, still play crucial roles in growing networks with geographical meas...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6594996/ https://www.ncbi.nlm.nih.gov/pubmed/31243325 http://dx.doi.org/10.1038/s41598-019-45783-y |
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author | Zhang, Li-Sheng Li, Chun-Lei |
author_facet | Zhang, Li-Sheng Li, Chun-Lei |
author_sort | Zhang, Li-Sheng |
collection | PubMed |
description | Many practical networks, such as city networks, road networks and neural networks, usually grow up on basis of topological structures and geographical measures. Big hubs, importance of which have been well known in complex networks, still play crucial roles in growing networks with geographical measures. Therefore, it is very necessary to investigate the underlying mechanisms of statistical features of different top hubs in such networks. Here, we propose a growing network model based on optimal policy in geographical ground. Through the statistics of a great number of geographical networks, we find that the degree and position distributions of top four hubs are diverse between them and closely interrelated with each other, and further gain the relationships between the upper limits of top hubs and the size of networks. Then, the underlying mechanisms are explored. Meanwhile, we are diligent to obtain the corresponding relationships of different spatial distribution areas for different top hubs, and compute their abnormal average degrees at different spatial positions, which show significant differences and imply the advantage of spatial positions and intense competition between top hubs. We hope our results could offer useful inspirations for related practical network studies. |
format | Online Article Text |
id | pubmed-6594996 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65949962019-07-03 The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy Zhang, Li-Sheng Li, Chun-Lei Sci Rep Article Many practical networks, such as city networks, road networks and neural networks, usually grow up on basis of topological structures and geographical measures. Big hubs, importance of which have been well known in complex networks, still play crucial roles in growing networks with geographical measures. Therefore, it is very necessary to investigate the underlying mechanisms of statistical features of different top hubs in such networks. Here, we propose a growing network model based on optimal policy in geographical ground. Through the statistics of a great number of geographical networks, we find that the degree and position distributions of top four hubs are diverse between them and closely interrelated with each other, and further gain the relationships between the upper limits of top hubs and the size of networks. Then, the underlying mechanisms are explored. Meanwhile, we are diligent to obtain the corresponding relationships of different spatial distribution areas for different top hubs, and compute their abnormal average degrees at different spatial positions, which show significant differences and imply the advantage of spatial positions and intense competition between top hubs. We hope our results could offer useful inspirations for related practical network studies. Nature Publishing Group UK 2019-06-26 /pmc/articles/PMC6594996/ /pubmed/31243325 http://dx.doi.org/10.1038/s41598-019-45783-y Text en © The Author(s) 2019 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 http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhang, Li-Sheng Li, Chun-Lei The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy |
title | The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy |
title_full | The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy |
title_fullStr | The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy |
title_full_unstemmed | The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy |
title_short | The Statistical Analysis of Top Hubs in Growing Geographical Networks with Optimal Policy |
title_sort | statistical analysis of top hubs in growing geographical networks with optimal policy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6594996/ https://www.ncbi.nlm.nih.gov/pubmed/31243325 http://dx.doi.org/10.1038/s41598-019-45783-y |
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