基于度的图熵递减值的图运算

IF 2.9 2区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Match-Communications in Mathematical and in Computer Chemistry Pub Date : 2022-08-01 DOI:10.46793/match.89-2.405y
Jingzhi Yan, Feng Guan
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引用次数: 0

摘要

基于度的图熵Id是由图的顶点度定义的信息函数衍生而来的参数度量,用于表征复杂网络的结构。由于缺乏有效的方法来分析最小图的性质,确定最小图的最小值是具有挑战性的。本文研究了(n, m)-图中图熵的最小性质,并定义了两种新的图熵运算,它们可以减小图熵的值。
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Graph Operations Decreasing Values of Degree-Based Graph Entropies
The degree-based graph entropy Id is a parametric measure derived from an information functional defined by vertex degrees of a graph, which is used to characterize the structure of complex networks. Determining minimal values of Id is challenging due to a lack of effective methods to analyze properties of minimal graphs. In this paper, we investigate minimal properties of the graph entropy in (n, m)-graphs and define two new graph operations, which can decrease the values of Id.
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来源期刊
CiteScore
4.40
自引率
26.90%
发文量
71
审稿时长
2 months
期刊介绍: MATCH Communications in Mathematical and in Computer Chemistry publishes papers of original research as well as reviews on chemically important mathematical results and non-routine applications of mathematical techniques to chemical problems. A paper acceptable for publication must contain non-trivial mathematics or communicate non-routine computer-based procedures AND have a clear connection to chemistry. Papers are published without any processing or publication charge.
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