Abstract
Ancient glass stored underground for a long time has undergone different degrees of weathering, which has led to changes in its chemical composition and affected the correct judgment of its category. Based on this, this paper uses various algorithms such as Spearman correlation coefficient, chi-square test and cluster analysis to establish a comprehensive model for glass composition evaluation. The results show that: (1) The surface weathering degree of glass artifacts is significantly correlated with their types; (2) The content of Lead oxide can be used to make a general distinction between high-potassium glass and lead-barium glass; (3) Among the known glass samples, high-potassium glass can be divided into three categories and lead-barium glass can be divided into four categories; (4) According to the reasonableness test, it is known that the model has good reliability and can provide guidance for the study of ancient glass.
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