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首页> 外文期刊>Journal of Chemistry >Computing Eccentricity-Based Topological Indices of 2-Power Interconnection Networks
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Computing Eccentricity-Based Topological Indices of 2-Power Interconnection Networks

机译:计算基于偏心的2电源互连网络拓扑指标

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摘要

In a connected graph G with a vertex v, the eccentricity εv of v is the distance between v and a vertex farthest from v in the graph G. Among eccentricity-based topological indices, the eccentric connectivity index, the total eccentricity index, and the Zagreb index are of vital importance. The eccentric connectivity index of G is defined by ξG?=?∑v∈VGdvεv, where dv is the degree of the vertex v and εv is the eccentricity of v in G. The topological structure of an interconnected network can be modeled by using graph explanation as a tool. This fact has been universally accepted and used by computer scientists and engineers. More than that, practically, it has been shown that graph theory is a very powerful tool for designing and analyzing the topological structure of interconnection networks. The topological properties of the interconnection network have been computed by Hayat and Imran (2014), Haynes et al. (2002), and Imran et al. (2015). In this paper, we compute the close results for eccentricity-based topological indices such as the eccentric connectivity index, the total eccentricity index, and the first, second, and third Zagreb eccentricity index of a hypertree, sibling tree, and X-tree for k-level by using the edge partition method.
机译:在具有顶点V的连接图G中,V的偏心εv是V的V和顶点之间的距离,在图表G中的V.基于偏心的拓扑指数,偏心连接指数,总偏心指数以及萨格勒布指数重要性至关重要。 G的偏心连接指数由ξg?=σv∈vgdvεv定义,其中dv是顶点V和εv的程度是G中V的偏心率。可以通过使用图来建模互连网络的拓扑结构作为工具的说明。这一事实已被计算机科学家和工程师普遍接受和使用。实际上,已经表明图表理论是设计和分析互连网络的拓扑结构的一个非常强大的工具。互连网络的拓扑特性已经由Haynat和Imran(2014)计算,Haynes等人。 (2002)和Imran等人。 (2015)。在本文中,我们计算基于偏心的拓扑指数的关闭结果,例如偏心连接指数,总偏心率指数,以及高文,兄弟树和X树的第一,第二和第三萨格勒布偏心指数k级使用边缘分区方法。

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