Abstract:
: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.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Ma J,Shi Y,Wang Z,Yue Jdoi
10.1038/srep19066subject
Has Abstractpub_date
2016-01-11 00:00:00pages
19066issn
2045-2322pii
srep19066journal_volume
6pub_type
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