Abstract
Glass is a valuable material evidence of the ancient Silk Road between China and the West, but it is easily weathered by environmental factors due to its long history. Weathering causes changes in the internal chemical composition, which affects the correct judgment of the type of glass products. Therefore, the analysis and identification of glass cultural relics become the key problem to be solved. This paper mainly aims at the type and composition of ancient glass, establishes a multi-objective classification model and a multi latitude prediction model, and solves the problem of composition analysis and identification of ancient glass products,first, SPSS was used to fill in the missing values by sequence average method, and the outliers were eliminated by box chart inspection. The partial correlation analysis of glass surface weathering and its type, color and texture is carried out, and the correlation is obtained through the correlation coefficient analysis of glass surface weathering and the three. The statistical law of chemical composition content was obtained by using the data analysis of SPSS software. The content of chemical components before weathering is predicted and determined by the difference between the content of chemical components after weathering and the mean difference before and after weathering.
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