Composition analysis and identification of ancient glass products based on K-Means clustering analysis algorithm

Yijing Zhong; Yuhang Pei

doi:10.54097/hset.v44i.7338

Authors

Yijing Zhong
Yuhang Pei

DOI:

https://doi.org/10.54097/hset.v44i.7338

Keywords:

PYH-Topsis method; K-Means clustering; High potassium glass; Lead barium glass.

Abstract

Ancient glass is a valuable physical evidence of early trade exchanges, and it is very susceptible to weathering caused by the environmental impact of burial. Therefore, the establishment of a glass cultural relics identification model and the analysis of the chemical composition of glass cultural relics are extremely important for the classification and protection of cultural relics in our country. In this paper, we first use differential analysis to find out the chemical composition with significant differences before and after weathering, and obtain the classification laws of high potassium glass and lead-barium glass. Then the 14 chemical components of high potassium glass and lead-barium glass were analyzed by K-Means clustering, and finally 8 subclasses were divided. After testing, the model has low sensitivity, strong stability and good robustness. On this basis, the improved PYH-Topsis solution distance method is used to construct a judgment matrix, analyze the chemical composition of glass cultural relics of unknown categories, and identify the types to which they belong.

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