Academic Journal of Computing & Information Science, 2023, 6(4); doi: 10.25236/AJCIS.2023.060406.
Yeting Song, Yuzhu Mao, Yanrun Wang
Northwest Normal University, Lanzhou, Gansu, 730070, China
Ancient glass is easily affected by environmental weathering. In the process of weathering, the proportion of its chemical composition will change, thus affecting the accurate judgment of its category. Therefore, according to the information such as surface weathering degree, type, color and pattern, Spearman correlation coefficient is used to conduct correlation analysis on the chemical composition of weathered cultural relics. Therefore, according to the information such as surface weathering degree, type, color and pattern, Spearman correlation coefficient is used to conduct correlation analysis on the chemical composition of weathered cultural relics, K-means clustering algorithm and decision tree are used to explore the classification rules of glass cultural relics and subcategory division of glass cultural relics [1], which is of vital importance for the study of ancient glass cultural relics.
Composition analysis of glass relics, Spearman correlation coefficient, Decision tree classification, K-means clustering algorithm
Yeting Song, Yuzhu Mao, Yanrun Wang. Component analysis and sub-classification of glass relics based on machine learning. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 4: 49-56. https://doi.org/10.25236/AJCIS.2023.060406.
[1] Gan Fuxi. The Origin and development of glass in ancient China [M]. Chinese Journal of Nature. 2006. 28(004):187-193.
[2] Jia Xiaofen, Guo Yongsheng, Huang Yourui. Salt and pepper noise detection algorithm for color images based on Spearman rank correlation [J]. Journal of University of Science and Technology of China. 2019. 49(001):63-70.
[3] Zhou Nan. Case Study of Prediction Analysis Based on Multiple Linear Regression Model [J]. Enterprise Review. 2013 48(009):122-154.
[4] Si Dajun, Hu Wenyue, Deng Zilin, Xu Yanhui. Fair hierarchical clustering of substations based on Gini coefficient [J].Global Energy Interconnection. 2021.04(006):12-16.
[5] Dong Shirong. Application of linear regression method of K-mean cluster analysis in correlation analysis [J]. Journal of Changchun Normal University. 2018.25 (008): 62-66.
[6] Yang Zhenzhen, Li Hongyao, Yang Keyi, Liu Lin. Clustering Analysis of Residents' Consumption Level Based on Systematic Clustering Algorithm and Elbow Criterion [J]. China Science and Technology Information. 2021. 16(012):121-122.
[7] Li Mingmei. Research on Fusion clustering method based on data feature selection [D]. Hangzhou Dianzi University. 2022.