Glass Classification Accuracy Based on Spearman Coefficient and K-Means ++ Algorithm
DOI:
https://doi.org/10.54097/e89bys55Keywords:
Glass, Chemical Composition, Classification, K-means++, Spearman Coefficient.Abstract
The study of the physical and chemical properties of artifactual glass can contribute greatly to the attribution of artifacts and to the study of their history. In this paper, we study the interplay of physical and chemical properties of glass and classify them. In order to make the classification more accurate, the correlation coefficients of compounds were calculated using Spearman's coefficient, and the content of lead oxide was determined as the basis for the classification. After that, this paper used K-means++ to cluster the data and selected calcium oxide and alumina as the sub-classification basis for high-potassium glass, and lead oxide and barium oxide as the sub-classification basis for lead-barium glass. Finally, the contents of some artifacts calcium oxide, alumina, lead oxide and barium oxide were changed with a perturbation of 0.2%, and the clustering points did not move significantly, and the model was stable.
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Wu Chi,Fu Xingyao,Shi Jinlong,Liu Quanwei. Research on Chemical Composition and Weathering of Ancient Glass Based on Grey Correlation[J]. Journal of Physics: Conference Series,2023,2508(1).
Jiang Yicheng,Wang Yu,Chen Shuai,Liu Zhixin,Yang Haojun,Jiao Yuwen,Tang Liming. Screening of Biomarkers in Liver Tissue after Bariatric Surgery Based on WGCNA and SVM-RFE Algorithms[J]. Disease Markers,2023,2023.
Zhu Manqin,Hu Shengbo,Yang Kai,Yan Tingting,Ye Lv,Li Hongjuan,Jin Yang. GMSK Demodulation Combining 1D‐CNN and Bi‐LSTM Network Over Strong Solar Wind Turbulence Channel[J]. Radio Science,2023,58(1).
Zaheer Shahzad,Anjum Nadeem,Hussain Saddam,Algarni Abeer D.,Iqbal Jawaid,Bourouis Sami,Ullah Syed Sajid. A Multi Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model[J]. Mathematics,2023,11(3).
Han Dongyang,Liu Pan,Xie Kang,Li He,Xia Qian,Cheng Qian,Wang Yibo,Yang Zhikai,Zhang Yanjun,Xia Jun. An attention-based LSTM model for long-term runoff forecasting and factor recognition[J]. Environmental Research Letters,2023,18(2).
Vilarinho R,Weber M C,Guennou M,Miranda A C,Dias C,Tavares P,Kreisel J,Almeida A,Moreira J Agostinho. Author Correction: Magnetostructural coupling in RFeO3 (R = Nd, Tb, Eu and Gd).[J]. Scientific reports,2023,13(1).
Zou Ying. Molecular-Composition Analysis of Glass Chemical Composition Based on Time-Series and Clustering Methods[J]. Molecules,2023,28(2).
Singh Sanjeet,Bansal Pooja,Hosen Mosharrof,Bansal Sanjeev K.. Forecasting annual natural gas consumption in USA: Application of machine learning techniques- ANN and SVM[J]. Resources Policy,2023,80.
Hu Junying,Qian Xiaofei,Tan Changchun,Liu Xinbao. Point and interval prediction of aircraft engine maintenance cost by bootstrapped SVR and improved RFE[J]. The Journal of Supercomputing,2022,79(7).
ThenObłuska Joanna,Dussubieux Laure. Beads from a mediaeval pilgrim centre: Chemical composition and provenance of glass from Banganarti, Nubia, Sudan[J]. Archaeometry,2022,65(2).
Zlámalová Cílová Zuzana,Blažková Gabriela. Chemical composition of early modern and modern window glass from archaeological excavations in Prague‐Hradčany, Czech Republic[J]. Archaeometry,2022,64(6).
Tkaczewska Ewelina. Effect of Chemical Composition and Network of Fly Ash Glass on the Hydration Process and Properties of Portland-Fly Ash Cement[J]. Journal of Materials Engineering and Performance,2021,30(12).
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