Huang Rongbing, Hanif Muhammad Farhan, Siddiqui Muhammad Kamran, Hanif Muhammad Faisal, Petros Fikre Bogale
School of Computer Science, Chengdu University, Chengdu, China.
Department of Mathematics and Statistics, The University of Lahore, Lahore, Pakistan.
Sci Rep. 2024 Nov 4;14(1):26552. doi: 10.1038/s41598-024-77838-0.
In the current age of chemical science, chemical graph theory has significantly advanced our understanding of the characteristics of chemical compounds. To simulate the mathematical, chemical, and physical aspects of networks, a topological index, a numerical measure obtained from the graph of a chemical network, employed. Recent work has explored the topological properties of boron oxide using chemical graph theory. In this work, we conduct a Pearson correlation analysis of boron oxide to assess the correlations between the Van and S indices and entropy metrics. We analyze the Pearson correlation coefficients between the entropy values and the calculated indices using a heatmap. In this article, a significant positive correlation between the Van, and S indices, and entropy values, which is represented by the heatmap of the strong linear correlations. To avoid duplication, a dimensionality reduction technique should be used for highly connected variables. Additionally, this study gives a detailed explanation of the link between the indices and entropy, which will form the basis of further statistical investigations.
在当今化学科学时代，化学图论极大地增进了我们对化合物特性的理解。为了模拟网络的数学、化学和物理方面，采用了一种拓扑指数，即从化学网络的图中获得的一种数值度量。最近的研究利用化学图论探索了氧化硼的拓扑性质。在这项工作中，我们对氧化硼进行了皮尔逊相关分析，以评估范指数和S指数与熵度量之间的相关性。我们使用热图分析熵值与计算出的指数之间的皮尔逊相关系数。在本文中，范指数、S指数与熵值之间存在显著的正相关，这由强线性相关性的热图表示。为避免重复，对于高度相关的变量应使用降维技术。此外，本研究对指数与熵之间的联系给出了详细解释，这将构成进一步统计研究的基础。
