Academic Journal of Materials & Chemistry, 2023, 4(1); doi: 10.25236/AJMC.2023.040110.
Yaxuan Zhang1, Yilin Chen2
1School of Computer Science, Nanjing University of Information Science and Technology, Nanjing, 210044, China
2School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
Glass is one of the first artificial materials invented by mankind, and its development has a long history. Glass production is usually locally sourced, and the glass-making process is similar in different regions, but the chemical composition is different. Ancient glass is highly susceptible to weathering by the burial environment. During the weathering process, a large number of internal elements are exchanged with environmental elements, resulting in changes in its composition ratio, which affects the correct judgment of its category. This paper has analyzed the content and correlation of its chemical components, and used principal component analysis and least squares multiple linear regression to realize the classification of glass type subclasses.
Antique glassware; Multiple linear regression; Hierarchical clustering model
Yaxuan Zhang, Yilin Chen. Subclass classification and chemical composition analysis and identification of ancient glass products. Academic Journal of Materials & Chemistry (2023) Vol. 4, Issue 1: 54-61. https://doi.org/10.25236/AJMC.2023.040110.
 Chen Shuyu. The origin and development of ancient glass in China [J]. Cultural Identification and Appreciation, 2019(4): 44-45.
 Zhou Jing. Glass trade on the Silk Road and the eastern transmission of glass manufacturing technology [J]. Journal of Suzhou College of Arts and Crafts, 2017(4): 15-18.
 Gao Shan. Silk Road glass was once considered a treasure by the Chinese [J]. World Culture, 2018(8): 40-41.
 Jing Zhongquan, Jiang Xiuhui et al. Research on the index system of coal mine safety production capacity based on hierarchical analysis (APH) [J]. China Journal of Safety Science. 2006,16(9): 74-79
 Ma Xiuhong, Song Jianshe, Dong Shengfei. Exploration of decision trees in data mining [J]. Computer Engineering and Applications, 2004, (2): 133-135.