论文标题
随机蜘蛛树的拓扑指数研究中的概率方法
Probabilistic Methods in the Study of Topological Indices on Random Spider Trees
论文作者
论文摘要
在本文中,我们表征了一类随机蜘蛛树(RST)的结构和拓扑指数,例如基于学位的Gini指数,基于学位的胡佛指数,广义Zagreb索引以及与这些相关的其他指数。我们通过概率方法获得了叶子数量的确切和渐近分布。此外,我们将此模型与以优先依恋方式演变的RST类相关联。
In this paper, we characterize the structure and topological indices of a class of random spider trees (RSTs) such as degree-based Gini index, degree-based Hoover index, generalized Zagreb index and other indices associated with these. We obtain the exact and asymptotic distributions of the number of leaves via probabilistic methods. Moreover, we relate this model to the class of RSTs that evolves in a preferential attachment manner.