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ORIGINAL RESEARCH article
Front. Mater.
Sec. Polymeric and Composite Materials
Volume 11 - 2024 |
doi: 10.3389/fmats.2024.1454935
Prediction of thermal protection performance and empirical study of flame-retardant cotton based on a combined model
Provisionally accepted- 1 Zhejiang College of Security Technology, Wenzhou, Zhejiang Province, China
- 2 Wenzhou Darong Textile Instrument Co., Ltd., Wenzhou, China
- 3 Zhejiang Institute of Metrology, Hangzhou, Zhejiang Province, China
- 4 China Jiliang University, Hangzhou, China
- 5 Zhejiang Light Industrial Products Inspection and Research Institute, Hangzhou, China
Thermal protection performance (TPP) is an important index to evaluate the performance of firefighting clothing. The purpose of this work is to build a model to predict the TPP values of fabrics with fewer variables. Two properties of flame-retardant cotton were tested with TPP values under different air gaps, and the correlations between these properties were also analyzed. A combined model was established by integrating multivariate nonlinear regression model and gradient boosting regression tree model. Then the combined model was compared with these two single models. The results showed that the correlation coefficients between gram weight and thickness of fabric and TPP value were 0.833 and 0.837, respectively, indicating a strong correlation. The correlation coefficient between air gap and TPP value was 0.304, indicating a weak correlation. In predicting the thermal protective performance of flame-retardant cotton, this study employed a multivariate nonlinear regression model, a Gradient Boosting Regression Tree (GBRT) model, and a combined model. After comparing various evaluation metrics, it was finally decided to adopt the combined model for predicting the thermal protective performance values of flame-retardant cotton. This method improved the prediction accuracy of thermal protective performance, facilitating the promotion and application of the combined model. Furthermore, when exploring the thermal protective performance of flame-retardant cotton, the use of fewer variables to establish the prediction model can not only significantly simplify the complex structure of the model but also greatly enhance the analysis efficiency, ensuring the efficiency and precision of the research process.
Keywords: Flame-retardant cotton, Thermal protection performance, Multivariate nonlinear regression, Gradient boosting regression tree, Combined model
Received: 27 Jun 2024; Accepted: 02 Sep 2024.
Copyright: © 2024 Zhang, Ma, Wang, Zhang, Ye, Zhang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Haihang Li, China Jiliang University, Hangzhou, China
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