Study on the correlation degree of chemical elements of glass based on grey theory

Lin Zhang, Tingting Yan, Dongyang Xi, Xiaodan Wang
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Abstract

In order to classify glass samples with known chemical composition, this paper adopts K-Means clustering analysis algorithm. By distinguishing the main element content of the two kinds of glass, we have made a subclassification under the major category. The high potassium glass is divided into high silica low potassium oxide group and low silica high potassium oxide group. Lead barium glass can be divided into low barium oxide low phosphorus pentoxide group and high barium oxide high phosphorus pentoxide group. Therefore, after the content of various elements of various glass is obtained, the grey correlation analysis model is used to make the data of each chemical component as the parent sequence and the other chemical components as the sub-sequence to solve the grey correlation coefficient of pair chemical components successively, so as to further analyze the correlation between their chemical components. Therefore, after the completion of the subclassification, it is helpful for archaeologists to distinguish the glass cultural relics after weathering. With the analysis of grey relational degree, the composition relationship of ancient glass relics can be further explored.
基于灰色理论的玻璃化学元素关联度研究
为了对化学成分已知的玻璃样品进行分类,本文采用K-Means聚类分析算法。通过区分两种玻璃的主要元素含量,我们在大类下做了一个小分类。高钾玻璃分为高硅低氧化钾基团和低硅高氧化钾基团。铅钡玻璃可分为低氧化钡低五氧化二磷基团和高氧化钡高五氧化二磷基团。因此,在获得各种玻璃的各种元素含量后,采用灰色关联分析模型,将每种化学成分的数据作为父序列,其他化学成分作为子序列,依次求解成对化学成分的灰色关联系数,从而进一步分析其化学成分之间的相关性。因此,在完成分类后,有助于考古学家对风化后的玻璃文物进行区分。通过灰色关联度分析,可以进一步探索古代玻璃文物的成分关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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