Academic Journal of Materials & Chemistry, 2023, 4(1); doi: 10.25236/AJMC.2023.040109.
Haiyu Wang, Jiashu Zhai, Wujun Tao
College of Mathematical Science and Engineering, Hebei University of Engineering, Handan, Hebei, 056038, China
In this paper, the surface weathering, type, decoration, color and content of each chemical component of glass artifacts were studied and analyzed, and a K-means clustering model was established, using Spearman correlation analysis, chi-square test, and. It was solved to classify the glass types and analyze the change pattern of chemical composition of glass artifacts, and a better fitting effect was obtained. This paper characterized the problem as a prediction class, firstly, assigned values to four categorical variables: surface weathering, type, decoration and color of glass artifacts, and then used spss to perform Spearman correlation and chi-square test analysis to pre-process the data and eliminate invalid data. Then, it used descriptive statistical analysis to find that most of the chemical components of high potassium glass showed a decreasing trend after weathering, and most of the chemical components of lead-barium glass showed an increasing trend after weathering; finally, used Matlab matrix to derive a linear mapping relationship based on the changes of chemical components before and after weathering, and finally predicted the chemical components of glass artifacts before weathering.
Antique glassware; K-means clustering model; Chi-square test; Spearman correlation
Haiyu Wang, Jiashu Zhai, Wujun Tao. Prediction of the chemical composition content of ancient glass artifacts before weathering. Academic Journal of Materials & Chemistry (2023) Vol. 4, Issue 1: 48-53. https://doi.org/10.25236/AJMC.2023.040109.
[1] Bo YH, Yan ZQ, Wang ZP, Zheng CH. Study on the preparation of C4 olefins based on multiple regression model [J]. Science and Technology Innovation, 2022(11): 49-52.
[2] Li Chunsheng, Yu Hu. Construction of vehicle driving conditions based on improved K-means clustering algorithm [J]. Computer Technology and Development, 2022, 32(03): 169-174.
[3] Chen Guiru, Wang Bing, Cao Zhijie, Wang Shaoping. Research on wind power prediction based on clustering analysis and optimization neural network [J]. Electrical Automation, 2020, 42(03): 24-27.
[4] Liu Z , Liu Y , Xing H , et al. Determination of the Content of Pectin and Hemicellulose in Ramie Based on Near-infrared Technique[J]. Plant Fiber Sciences in China, 2018.
[5] Liang T, Zhou N, Lu TQ, Wu H, Ju P. Parameter filling method and typical parameter analysis of induction motor load transient model [J]. Power System Automation, 2020, 44(01): 74-82.