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Academic Journal of Computing & Information Science, 2024, 7(10); doi: 10.25236/AJCIS.2024.071011.

Prediction of Surface Weathering of Glass Artifacts Based on Multi-Factor Analysis

Author(s)

Han Lin

Corresponding Author:
Han Lin
Affiliation(s)

College of Mathematics and Computer Science, Shantou University, Shantou, 515063, China

Abstract

Glass artifacts hold significant importance in historical and cultural heritage; however, their surface weathering presents challenges for preservation and research. This study aims to analyze the mechanisms and influencing factors of surface weathering of glass artifacts. By classifying glass artifacts based on color, texture, and glass type, the weathering rates of different groups were calculated and compared. The TOPSIS model and entropy weight method were used to evaluate the weight of each factor's impact on the weathering rate and to develop a predictive model. The results indicate that glass type has the greatest impact on the weathering rate, followed by color and decoration type. Through statistical analysis of chemical composition, six elements—silicon, sodium, aluminum, lead, phosphorus, and strontium—were identified as having significant effects on weathering. The final predictive model demonstrated an accuracy of approximately 73%. This study not only provides new analytical methods and predictive models but also offers a scientific basis for conservation and restoration efforts.

Keywords

Glass artifacts, Surface weathering, TOPSIS model, Entropy weight method, Chemical composition analysis

Cite This Paper

Han Lin. Prediction of Surface Weathering of Glass Artifacts Based on Multi-Factor Analysis. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 10: 76-81. https://doi.org/10.25236/AJCIS.2024.071011.

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