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Research on composition analysis and type identification of ancient glass products based on data mining

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DOI: 10.23977/autml.2022.030210 | Downloads: 38 | Views: 972

Author(s)

Chang Su 1, Jingjing Wang 2

Affiliation(s)

1 School of Information Management & Engineering, Shanghai University of Finance and Economics, Shanghai, 200433, China
2 School of Mathematics, Shanghai University of Finance and Economics, Shanghai, 200433, China

Corresponding Author

Chang Su

ABSTRACT

The ancient glass products are easy to be weathered, which makes a large number of internal and external elements exchange, leading to the change of their composition proportion, which further affects the composition analysis and identification. This paper establishes a mathematical model based on the weathering phenomenon of ancient glass products in China and the related chemical composition data, to predict, analyze and solve the classification laws and classification results of different glasses, the statistical laws and correlation of chemical composition content, and other problems.

KEYWORDS

Chi-square test, decision tree, cluster analysis, BP neural network, grey correlation analysis

CITE THIS PAPER

Chang Su, Jingjing Wang, Research on composition analysis and type identification of ancient glass products based on data mining. Automation and Machine Learning (2022) Vol. 3: 63-72. DOI: http://dx.doi.org/10.23977/autml.2022.030210.

REFERENCES

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