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.
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