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The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products
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摘要 Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on. Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.
作者 Jenny Zhang Ding Li Yu Xie Junfeng Xiang Jenny Zhang;Ding Li;Yu Xie;Junfeng Xiang(School of Energy and Power Engineering, Jiangsu University, Zhenjiang, China)
出处 《Open Journal of Applied Sciences》 2023年第11期2149-2171,共23页 应用科学(英文)
关键词 Principal Component Analysis System Clustering Sensitivity Analysis Binary Classification Model Logistic Regression Analysis Grey Correlation Analysis Principal Component Analysis System Clustering Sensitivity Analysis Binary Classification Model Logistic Regression Analysis Grey Correlation Analysis
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