Abstract
In ancient times fluxes were often added to the production of glass to lower the melting point of pure quartz sand. During the smelting process, the addition of different products resulted in significant changes in the internal composition of the glass products. This paper examines a sample of ancient glassworks, based on the data from several sources. The data are divided into 'weathered' and 'unweathered', and cluster analysis reveals significant differences between the categories, and random forest analysis is used to determine the non-linear relationship between the variables, resulting in a chemical composition correlation of the relationships were more variable for potassium chloride and lead chloride and smoother for the rest. This paper innovatively adopts a combination of K-means cluster analysis and random forest to evaluate the composition and identification problems of ancient glass objects. The model in this paper can also be extended to other studies related to the degree of weathering in ancient wooden shipwrecks, metals, ceramics, and other aspects.
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