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On Wiener polarity index of bicyclic networks
Complex networks are ubiquitous in biological, physical and social sciences. Network robustness research aims at finding a measure to quantify network robustness. A number of Wiener type indices have recently been incorporated as distance-based descriptors of complex networks. Wiener type indices ar...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4707490/ https://www.ncbi.nlm.nih.gov/pubmed/26750820 http://dx.doi.org/10.1038/srep19066 |
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author | Ma, Jing Shi, Yongtang Wang, Zhen Yue, Jun |
author_facet | Ma, Jing Shi, Yongtang Wang, Zhen Yue, Jun |
author_sort | Ma, Jing |
collection | PubMed |
description | Complex networks are ubiquitous in biological, physical and social sciences. Network robustness research aims at finding a measure to quantify network robustness. A number of Wiener type indices have recently been incorporated as distance-based descriptors of complex networks. Wiener type indices are known to depend both on the network’s number of nodes and topology. The Wiener polarity index is also related to the cluster coefficient of networks. In this paper, based on some graph transformations, we determine the sharp upper bound of the Wiener polarity index among all bicyclic networks. These bounds help to understand the underlying quantitative graph measures in depth. |
format | Online Article Text |
id | pubmed-4707490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47074902016-01-20 On Wiener polarity index of bicyclic networks Ma, Jing Shi, Yongtang Wang, Zhen Yue, Jun Sci Rep Article Complex networks are ubiquitous in biological, physical and social sciences. Network robustness research aims at finding a measure to quantify network robustness. A number of Wiener type indices have recently been incorporated as distance-based descriptors of complex networks. Wiener type indices are known to depend both on the network’s number of nodes and topology. The Wiener polarity index is also related to the cluster coefficient of networks. In this paper, based on some graph transformations, we determine the sharp upper bound of the Wiener polarity index among all bicyclic networks. These bounds help to understand the underlying quantitative graph measures in depth. Nature Publishing Group 2016-01-11 /pmc/articles/PMC4707490/ /pubmed/26750820 http://dx.doi.org/10.1038/srep19066 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ma, Jing Shi, Yongtang Wang, Zhen Yue, Jun On Wiener polarity index of bicyclic networks |
title | On Wiener polarity index of bicyclic networks |
title_full | On Wiener polarity index of bicyclic networks |
title_fullStr | On Wiener polarity index of bicyclic networks |
title_full_unstemmed | On Wiener polarity index of bicyclic networks |
title_short | On Wiener polarity index of bicyclic networks |
title_sort | on wiener polarity index of bicyclic networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4707490/ https://www.ncbi.nlm.nih.gov/pubmed/26750820 http://dx.doi.org/10.1038/srep19066 |
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