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  4. Vol 2, Issue 1, 2023

Research on Glass Weathering and Classification Problems in Ancient Times

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DOI: 10.23977/corwm.2023.020101 | Downloads: 5 | Views: 575

Author(s)

Yiqi Luo 1

Affiliation(s)

1 School of Computer Science and Engineering, Southwest Minzu University, Chengdu, 610041, China

Corresponding Author

Yiqi Luo

ABSTRACT

Glasses in ancient times tend to suffer from weathering when they are buried because of changes of the environment, which will affect the accurate judgment of its classification. This paper analyzes related data of ancient glass products in ancient times of China provided by 2022 National Mathematical Contest in Modeling for College Students and predicts their chemical composition contents before the weathering according to the statistical rules of chemical composition contents of the samples. A BP neural network model is built to analyze classification characteristics of high-potassium and lead barium glass. Besides, the entropy weight method and the clustering method are used together to subdivide two types of high-potassium and lead-barium glasses. It is hoped that this research can provide some reference for the composition analysis and category identification of ancient glass products.

KEYWORDS

Entropy weight method; clustering method; BP neural network

CITE THIS PAPER

Yiqi Luo, Research on Glass Weathering and Classification Problems in Ancient Times. Corrosion and Wear of Materials (2023) Vol. 2: 1-11. DOI: http://dx.doi.org/10.23977/corwm.2023.020101.

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