Abstract
The Silk Road was an important channel for economic exchanges between China and foreign countries in ancient times, and glass products were an important physical evidence of trade exchanges. Early glass was introduced to China in the form of bead-shaped products, and on this basis, craftsmen improved it to form the unique ancient Chinese glass. Glass products are important physical evidence of the ancient Silken Road, but they are vulnerable to weathering due to the influence of the burial environment. In this paper, we use a batch of ancient glass artifacts as the research object, and build a machine learning classification model and a clustering model based on the different chemical composition content to analyze the classification basis and the relationship between the chemical composition content of the glass artifacts and optimize the research.
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