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Topology Universality and Dissimilarity in a Class of Scale-Free Networks

We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extended models are evolved based on competition and inner anti-preferential deletion in growth and preferential attachment processes. By nonlinear and dynamic controlling on randomness and determinacy, thr...

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Detalles Bibliográficos
Autores principales: Zhang, Lanhua, Chen, Juan, Wang, Mei, Li, Yujuan, Xue, Shaowei, Tang, Yiyuan, Sun, Baoliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999222/
https://www.ncbi.nlm.nih.gov/pubmed/27560938
http://dx.doi.org/10.1371/journal.pone.0161653
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author Zhang, Lanhua
Chen, Juan
Wang, Mei
Li, Yujuan
Xue, Shaowei
Tang, Yiyuan
Sun, Baoliang
author_facet Zhang, Lanhua
Chen, Juan
Wang, Mei
Li, Yujuan
Xue, Shaowei
Tang, Yiyuan
Sun, Baoliang
author_sort Zhang, Lanhua
collection PubMed
description We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extended models are evolved based on competition and inner anti-preferential deletion in growth and preferential attachment processes. By nonlinear and dynamic controlling on randomness and determinacy, three models can self-organize into scale-free networks, and diverse scaling exponents appear. Moreover, the model with more determinacy has more stringent parameter control than randomness, especially in the edge deletion. Our results suggest that the nature of the topology universality and dissimilarity in SF networks may be the subtle changes of randomness and determinacy.
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spelling pubmed-49992222016-09-12 Topology Universality and Dissimilarity in a Class of Scale-Free Networks Zhang, Lanhua Chen, Juan Wang, Mei Li, Yujuan Xue, Shaowei Tang, Yiyuan Sun, Baoliang PLoS One Research Article We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extended models are evolved based on competition and inner anti-preferential deletion in growth and preferential attachment processes. By nonlinear and dynamic controlling on randomness and determinacy, three models can self-organize into scale-free networks, and diverse scaling exponents appear. Moreover, the model with more determinacy has more stringent parameter control than randomness, especially in the edge deletion. Our results suggest that the nature of the topology universality and dissimilarity in SF networks may be the subtle changes of randomness and determinacy. Public Library of Science 2016-08-25 /pmc/articles/PMC4999222/ /pubmed/27560938 http://dx.doi.org/10.1371/journal.pone.0161653 Text en © 2016 Zhang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zhang, Lanhua
Chen, Juan
Wang, Mei
Li, Yujuan
Xue, Shaowei
Tang, Yiyuan
Sun, Baoliang
Topology Universality and Dissimilarity in a Class of Scale-Free Networks
title Topology Universality and Dissimilarity in a Class of Scale-Free Networks
title_full Topology Universality and Dissimilarity in a Class of Scale-Free Networks
title_fullStr Topology Universality and Dissimilarity in a Class of Scale-Free Networks
title_full_unstemmed Topology Universality and Dissimilarity in a Class of Scale-Free Networks
title_short Topology Universality and Dissimilarity in a Class of Scale-Free Networks
title_sort topology universality and dissimilarity in a class of scale-free networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4999222/
https://www.ncbi.nlm.nih.gov/pubmed/27560938
http://dx.doi.org/10.1371/journal.pone.0161653
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