Study on the Composition Analysis and Identification of Ancient Glass Products

Authors

  • Shirui Li

DOI:

https://doi.org/10.54097/hset.v33i.5286

Keywords:

Correlation analysis, Clustering algorithm, T test, Random forest.

Abstract

The Silk Road was an important channel for cultural exchanges between ancient China and the West, and glass was a precious material evidence of early trade exchanges. Early glass was often made into ornaments and introduced into China. After absorbing its technology, ancient Chinese glass was made locally, similar to its appearance but different in chemical composition. Due to different fluxes added during refining, the glass can be divided into lead barium glass and potassium glass, ancient glass is easily weathered by burial environment. In the weathering process, due to a large amount of exchange between internal elements and external elements, the proportion of their components changes, which affects the correct judgment of their categories. The research on the relevant properties of ancient cultural relics is a major topic in the field of archaeology in China, which is of great significance. There are a number of relevant data on ancient glass products in China. Archaeologists have divided them into two types: high potassium glass and lead barium glass.In order to explore the relevant properties and chemical composition changes of these glass relics before and after weathering, this paper analyzes the classification rules of high potassium glass and lead barium glass; The classification results were analyzed for rationality and sensitivity.

Downloads

Download data is not yet available.

References

Wang Bo, Zhuang Jijun, Xiong Jun, Luo Xiaochen. Research on stochastic forest algorithm based on high-dimensional feature clustering optimization [J]. Journal of Jinggangshan University (Natural Science Edition), 2022,43 (05): 52-56

Sui Yong. Comprehensive evaluation of wheat inferior flour quality based on principal component and cluster analysis [J]. Modern Flour Industry, 2022,36 (02): 56

Spring flowers K-means clustering research based on swarm intelligence algorithm [D]. Dalian University of Technology, 2019. DOI: 10.26991/d.cnki.gdllu.2019.003511

Gong Yunqing, Tong Lichen, Yu Ze, Zhang Xu. Research on the method of rotating machinery misalignment fault diagnosis based on Pearson correlation coefficient [J]. China New Technology and New Product, 2022 (05): 48-50. DOI: 10.13612/j.cnki.cntp.2022.05.013

Li Jiakang, Tao Zhilin, Xu Bo, et al Quantitative analysis of tobacco leaf texture based on random forest [J] Hubei Agricultural Science, 2022,61 (14): 155-159. DOI: 10.14088/j.cnki.issn0439-8114.2022.14.028

Li Ruiguang, Duan Pengyu, Shen Meng, et al Traffic classification algorithm of Internet of Things devices based on random forest [J] Journal of Beijing University of Aeronautics and Astronautics, 2022,48 (2): 233-239. DOI: 10.13700/j.bh.1001-5965.2020.0383

Wang Bo, Zhuang Jijun, Xiong Jun, Luo Xiaochen. Research on stochastic forest algorithm based on high-dimensional feature clustering optimization [J]. Journal of Jinggangshan University (Natural Science Edition), 2022,43 (05): 52-56

Spring flowers K-means clustering research based on swarm intelligence algorithm [D]. Dalian University of Technology, 2019. DOI: 10.26991/d.cnki.gdllu.2019.003511

Gong Yunqing, Tong Lichen, Yu Ze, Zhang Xu. Research on the method of rotating machinery misalignment fault diagnosis based on Pearson correlation coefficient [J]. China New Technology and New Product, 2022 (05): 48-50. DOI: 10.13612/j.cnki.cntp.2022.05.013

Sui Yong. Comprehensive evaluation of wheat inferior flour quality based on principal component and cluster analysis [J]. Modern Flour Industry, 2022,36 (02): 56

Downloads

Published

21-02-2023

How to Cite

Li, S. (2023). Study on the Composition Analysis and Identification of Ancient Glass Products. Highlights in Science, Engineering and Technology, 33, 95-104. https://doi.org/10.54097/hset.v33i.5286