Study on Composition Analysis and Identification of Ancient Glass Products

Abstract

Glass is the precious material evidence of the early trade of the ancient Silk Road, but the ancient glass is easily weathered by the influence of burial, and its composition ratio changes, which affects the correct judgment of its category. The study of the composition analysis and identification of ancient glass products is of great help to understand the social culture and foreign trade civilization at that time. This paper mainly studies the composition analysis and identification of ancient glassware, to evaluate, predict and classify the ancient glassware, this paper establishes a comprehensive evaluation model, using the chi-square test, K-means clustering model, decision tree model, Lasso regression and grey correlation degree test. It helps archaeologists to analyze and predict the correlation between the weathering degree of cultural relics and their attributes and chemical composition content, and according to the existing classification standards of cultural relics. A labelled subclassification scheme is formulated to identify the types of unknown cultural relics. At the same time, the correlation between the chemical components of different types of cultural relics was analyzed.