Abstract The entropy-based procedures from the configuration of chemical graphs and multifaceted networks, several graph properties have been utilized. For computing, the organizational evidence of organic graphs and multifaceted networks, the graph entropies have converted the information-theoretic magnitudes. The graph entropy portion has attracted the research community due to its potential application in chemistry. In this paper, our input is to reconnoiter graph entropies constructed on innovative information function, which is the quantity of different degree vertices along with the quantity of edges between innumerable degree vertices.”In this study, we explore two dissimilar curricula of carbon nanosheets that composed by C4 and C8 denoted by T1C4C8(S)[m, n] and T2C4C8(R)[m, n]. Additionally, we calculate entropies of these configurations by creating a connection of degree-based topological indices with the advantage of evidence occupation.

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关于两个碳纳米片的基于度的熵的拓扑方面

摘要 来自化学图和多面网络配置的基于熵的程序，已经利用了几种图属性。对于计算，有机图和多面网络的组织证据，图熵已经转换了信息理论的量级。图熵部分因其在化学中的潜在应用而吸引了研究界。在本文中，我们的输入是重构基于创新信息函数构建的图熵，即不同度顶点的数量以及无数度顶点之间的边数量。”在这项研究中，我们探索了两种不同的碳纳米片课程由 C4 和 C8 组成，用 T1C4C8(S)[m, n] 和 T2C4C8(R)[m, n] 表示。此外，