Prediction and classification of chemical composition of ancient glass objects based on generalized Shapley functions
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View abstract on PubMed
Summary
This summary is machine-generated.This study develops a method to identify ancient glass by analyzing its chemical composition, even after weathering. The approach helps accurately categorize artifacts, aiding archaeological research.
Area Of Science
- Archaeometry
- Materials Science
- Analytical Chemistry
Background
- Ancient glass artifacts undergo chemical changes due to burial environments and weathering.
- These alterations complicate accurate identification and classification.
- Understanding chemical composition is crucial for archaeological provenance studies.
Purpose Of The Study
- To predict and identify the chemical composition of ancient glass products.
- To establish the relationship between weathering and glass type, decoration, and color.
- To develop a method for determining chemical composition before weathering for accurate artifact classification.
Main Methods
- Multivariate statistical ANOVA test to analyze factors influencing chemical composition.
- Data imputation for missing values and distance discrimination for weathering assessment.
- Gray prediction modeling and generalized Shapley function for composition analysis.
Main Results
- Identified laws governing chemical composition changes in weathered and unweathered ancient glass.
- Successfully predicted pre-weathering chemical composition using gray prediction.
- Quantified correlations and differences between various indicators and chemical compositions.
Conclusions
- The proposed scheme effectively addresses challenges in archaeological category judgment.
- Accurate chemical composition analysis aids in the identification of ancient glass.
- This method significantly contributes to advancing archaeological research and artifact analysis.
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