Computational analysis of Wollastonite graph structure via machine learning techniques
摘要
Wollastonite is a mineral named after English chemist W. H. Wollaston, which has applications in tiles, ceramics, polymers, plastic, rubber industry, paints, coatings, metallurgy, as construction materials in cement and insulation boards, and other uses. In this article, we study the abstract structure of Wollastonite from a combinatorial point of view, discuss its properties, and find its topological indices and the associated graph energy. We carry machine learning analysis of topological indices with the properties of Wollastonite graph by using the regression technique. The observation is that for higher order regression, an exact coefficient of determination is achieved; however, the third-order regression is practically more fit with the dataset.