Academic Journal of Computing & Information Science, 2022, 5(13); doi: 10.25236/AJCIS.2022.051310.
College of Science, Northeast Forestry University, Harbin, Heilongjiang Province, 150040, China
Glass products are an important material evidence of the early trade exchanges between China and the West. Under the influence of buried environment, the weathering of glass leads to the change of its chemical composition proportion, which then affects the judgment of cultural relic category. This paper analyzes and identifies the components of ancient glass products by combining sample data.In order to analyze the influencing factors of weathering of cultural relics samples, the paper analyzes the high potassium and lead barium glass types and observes the relationship between the pattern and color of the sample, and the whole chi square independence test is used to obtain the difference rules of glass category, decoration and color classification. For the chemical composition content prediction, the prediction model was built and predicted by the sample mean difference.In this paper, the chemical composition of the unknown category of glass relics was analyzed and identified by training on the valid data in Form 2. For the sensitivity of the classification results, the sensitivity formula was applied to calculate a sensitivity of 0.125.
Factor analysis method, K-means cluster, Fisher discrimination method, Gray association analysis
Ran Wang. Composition analysis and identification of ancient glass products. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 13: 62-68. https://doi.org/10.25236/AJCIS.2022.051310.
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