Compositional Analysis of Ancient Glassware Based on CRITIC Weighting Method and Superior Order Approximation Model

Abstract

Glass is a witness of early trade exchanges on the Silk Road. In this paper, based on the classification information of glass artefacts and their corresponding proportions of major components, the chi-square test, the CRITIC weighting method and the superior order approximation model are used. The data were first pre-processed to exclude the sample data whose sum of the proportions of chemical components did not belong to 85%~105%. After classifying the other glass artifacts according to their attributes, the chi-square test was carried out by SPSS, and according to the significance p-value <0.05, it was concluded that only the glass type within the three had a significant effect on the degree of weathering, while the decoration and colour had little effect on the degree of weathering. All the sample data were classified according to the combination of type-degree of differentiation, and then the CRITIC weight method was applied to find out the objective weight of each chemical indicator in the combination respectively, and finally the distribution of the weights of each chemical element in all the combinations was compared to establish a superior order approximation model, and the individuals whose predictive attributes were known according to the prediction attributes were taken as the prediction reference objects to obtain the final results.