Prediction of chemical composition of cultural relics glass based on moving average algorithm of least square method

Abstract

In order to explore the chemical composition of ancient cultural relics glass and understand the structure of ancient cultural relics glass, according to the basic information of glass cultural relics, the characteristics of glass are quantified, and the chi-square independence test is carried out on whether weathering and the properties of glass. Based on the cross table and chi-square test, it can be concluded that high potassium glass is generally not easy to weathering, while lead barium glass is more prone to weathering. A total of four categories were established to effectively reflect the statistical law of the chemical composition content of glass with different properties, and the principal component factors of each category were explored to obtain the chemical composition of each category. The scatter line diagram of the chemical composition of the unweathered sampling points was drawn. Based on the least square method, the ideal trend value of each chemical composition was calculated by using the moving average algorithm, and the prediction of various chemical compositions was completed. The chemical composition of the glass can be successfully predicted by the model constructed in this study. This method has certain technical support and theoretical support for the study of ancient glass, and provides some reference.