{"title":"Prediction of Chemical Composition of Ancient Glass Relics before Weathering","authors":"Jiehua Sun, Huazhou Chen, Yao Liu, Hongquan Lin, Huiwen Zheng, Yingzhen Qiu","doi":"10.4236/ojapps.2023.139124","DOIUrl":null,"url":null,"abstract":"Ancient glass relics are easily weathered by the influence of buried environment, and the internal elements exchange with the environmental elements in large quantities, resulting in changes in their composition ratio. Archaeological research can often detect the component content of glass relics after weathering, but it is difficult to obtain the corresponding component content before weathering. It is necessary to predict the chemical composition of glass relics before weathering in order to accurately identify the type of glass relics and repair them. To solve this problem, this paper proposes a distributed matching strategy, and studies the influence of weathering on the composition content of glass through compositional correlation analysis and linear regression statistical methods, so as to build a prediction model of the composition content of glass relics before weathering. The results show that the composition prediction model of glass cultural relics constructed by the distribution matching strategy has a good prediction ability, which is consistent with the change trend of the composition ratio of linear regression analysis. Moreover, the model is simple and easy to operate, which is convenient for popularization and application, and provides theoretical basis and reference value for further research on the composition and accurate classification of glass cultural relics.","PeriodicalId":19671,"journal":{"name":"Open Journal of Applied Sciences","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Journal of Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/ojapps.2023.139124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ancient glass relics are easily weathered by the influence of buried environment, and the internal elements exchange with the environmental elements in large quantities, resulting in changes in their composition ratio. Archaeological research can often detect the component content of glass relics after weathering, but it is difficult to obtain the corresponding component content before weathering. It is necessary to predict the chemical composition of glass relics before weathering in order to accurately identify the type of glass relics and repair them. To solve this problem, this paper proposes a distributed matching strategy, and studies the influence of weathering on the composition content of glass through compositional correlation analysis and linear regression statistical methods, so as to build a prediction model of the composition content of glass relics before weathering. The results show that the composition prediction model of glass cultural relics constructed by the distribution matching strategy has a good prediction ability, which is consistent with the change trend of the composition ratio of linear regression analysis. Moreover, the model is simple and easy to operate, which is convenient for popularization and application, and provides theoretical basis and reference value for further research on the composition and accurate classification of glass cultural relics.