Academic Journal of Materials & Chemistry, 2023, 4(5); doi: 10.25236/AJMC.2023.040503.
Chen Huang1, Bingzhou Bao2
1School of Material and Chemical Engineering, Anhui Jianzhu University, Hefei, 230601, China
2School of Computer and Information Technology, Anhui Normal University, Wuhu, 241002, China
The demand for face masks is on the rise due to the COVID-19 pandemic. Melt-blown nonwoven material is an important raw material for mask production, and its structural variables determine the performance of the final product. In this paper, the prediction model between structural variables and product performance is established, and the relationship between structural variables and product performance is obtained by using Gaussian process regression method, and the prediction model is tested to further verify the reliability of the model. The experimental results show that. The prediction accuracy of the model based on Gaussian process regression is high, and the average absolute error is less than 0.2, so the prediction method is effective. The final experimental results have a certain degree of reference significance for the study of the influence of the structure variables of intercalated melt-blown nonwovens on the product properties, which is helpful to provide a certain theoretical basis for the establishment of the control mechanism of product properties.
Structure variables; Properties of products; Gaussian process regression; Intercalated melt-blown nonwoven material
Chen Huang, Bingzhou Bao. Performance Study of Intercalated Meltblown Nonwoven Materials Based on Gaussian Process Regression. Academic Journal of Materials & Chemistry (2023) Vol. 4, Issue 5: 18-24. https://doi.org/10.25236/AJMC.2023.040503.
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