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.
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.