Prediction of thermal protection performance and empirical study of flame-retardant cotton based on a combined model

IF 2.6 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY
Siyuan Zhang, Keai Ma, Lijian Wang, Zhemin Zhang, Xiangyu Ye, Jinzhong Zhang, Haihang Li
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引用次数: 0

Abstract

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.
基于组合模型的阻燃棉热防护性能预测和实证研究
热防护性能(TPP)是评估消防服性能的一项重要指标。这项工作的目的是建立一个模型,用较少的变量来预测面料的 TPP 值。测试了阻燃棉的两种特性与不同气隙下的 TPP 值,并分析了这些特性之间的相关性。通过整合多元非线性回归模型和梯度提升回归树模型,建立了一个组合模型。然后将组合模型与这两个单一模型进行了比较。结果表明,织物的克重和厚度与 TPP 值的相关系数分别为 0.833 和 0.837,表明两者具有很强的相关性。气隙与 TPP 值的相关系数为 0.304,表明相关性较弱。在预测阻燃棉的热防护性能时,本研究采用了多元非线性回归模型、梯度提升回归树(GBRT)模型和组合模型。在对各种评价指标进行比较后,最终决定采用组合模型来预测阻燃棉的热防护性能值。这种方法提高了热防护性能的预测精度,有利于组合模型的推广和应用。此外,在探讨阻燃棉热防护性能时,使用较少的变量建立预测模型,不仅可以大大简化模型的复杂结构,还能大大提高分析效率,确保研究过程的高效性和精确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Materials
Frontiers in Materials Materials Science-Materials Science (miscellaneous)
CiteScore
4.80
自引率
6.20%
发文量
749
审稿时长
12 weeks
期刊介绍: Frontiers in Materials is a high visibility journal publishing rigorously peer-reviewed research across the entire breadth of materials science and engineering. This interdisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers across academia and industry, and the public worldwide. Founded upon a research community driven approach, this Journal provides a balanced and comprehensive offering of Specialty Sections, each of which has a dedicated Editorial Board of leading experts in the respective field.
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