Identification of the ancient glass analysis based on the logistics model and the SVM

Ran Ren; Xizhe Wei; Meini Liu; Nan Ling; Xiangdong Gu

doi:10.1117/12.2673017

14 April 2023 Identification of the ancient glass analysis based on the logistics model and the SVM

Ran Ren, Xizhe Wei, Meini Liu, Nan Ling, Xiangdong Gu

Proceedings Volume 12612, International Conference on Artificial Intelligence and Industrial Design (AIID 2022); 126120T (2023) https://doi.org/10.1117/12.2673017
Event: International Conference on Artificial Intelligence and Industrial Design (AIID 2022), 2022, Zhuhai, China

Abstract

In the trade of the ancient Chinese Silk Road, glass was a valuable material evidence of the early trade. However, the glass has experienced historical sand for a long time, and its surface is easily affected by the buried environment and weathering. In this paper, we will study the change of elements during weathering and identify and classify the glass based on the corresponding characteristics. Firstly, the component data of the ancient glass relics are processed uniformly, and the correlation analysis is conducted, and the model of the Logistics equation and the SVM subclassification model are trained and optimized with large lot of data to adjust to the best classification model, and the classification results. Through case analysis and comparative study of model results, it is shown that the classification model using potassium, silicon, lead and barium content as indicators has good applicability, accuracy and simplicity, which provides new ideas for the identification and analysis of the chemical composition of glass cultural relics.

Citation Download Citation

Ran Ren, Xizhe Wei, Meini Liu, Nan Ling, and Xiangdong Gu "Identification of the ancient glass analysis based on the logistics model and the SVM", Proc. SPIE 12612, International Conference on Artificial Intelligence and Industrial Design (AIID 2022), 126120T (14 April 2023); https://doi.org/10.1117/12.2673017

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