Author(s)

Yilei Wang ¹, Wenxuan Liu ², Ziqiang Lin ³

Affiliation(s)

¹ School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China
² School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China
³ School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 102616, China

Corresponding Author

Yilei Wang

ABSTRACT

To help ancient glass products to analyze and identify their components, this paper establishes a comprehensive evaluation model to help identify and analyze ancient glass products and their components, and classifies them according to the data, so as to clarify the correlation and sensitivity between their chemical elements. First, this paper makes a simple classification of the data, and then calculates several factors that account for a large proportion of the weight through principal component analysis (PCA). By reducing the dimension of data, the variables are reduced, making the classification basis more intuitive; At the same time, the factors that account for a large proportion of the main factors can be used as the intuitive basis for the division of subcategories. Finally, K-Means is used to further confirm the rationality and sensitivity of the relationship between specific factors and cultural relics.

KEYWORDS

Ancient glass products, Composition analysis and identification, K-Means, PCA, Sensitivity analysis

CITE THIS PAPER

Yilei Wang, Wenxuan Liu, Ziqiang Lin, Component Analysis and Identification Model of Ancient Glass Products Based on Correlation Analysis. Analytical Chemistry: A Journal (2022) Vol. 1: 75-83. DOI: http://dx.doi.org/10.23977/analc.2022.010110.

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