染整技术2025，Vol.47Issue(9)：29-31,3.
贝叶斯优化在功能性纺织品参数组合筛选中的应用
Application of Bayesian optimization in the selection of parameter combinations for functional textiles
牛欢1
作者信息
- 1. 西安外事学院商学院,陕西 西安 710077
- 折叠
摘要
Abstract
Faced with the core challenge of optimizing high-dimensional parameter combinations for functional textiles,Bayesian optimization technology,based on the self-learning mechanism of Gaussian processes,can actively identify Pareto optimal solutions that satisfy multiple constraints in the parameter space,overcoming the high cost and local optimization limitations of traditional trial-and-error methods.The case validation demonstrates that Bayesian optimization can precisely coordinate conflicting objectives such as waterproofing,moisture permeability,and cost control,driving the process window toward a high-performance,low-cost region.In the future,by integrating this technology and scaling it for industrial application,it can redefine the manufacturing paradigm for the textile industry.关键词
贝叶斯优化/功能性纺织品/参数组合/筛选Key words
Bayesian optimization/functional textiles/parameter combinations/screening分类
轻工纺织引用本文复制引用
牛欢..贝叶斯优化在功能性纺织品参数组合筛选中的应用[J].染整技术,2025,47(9):29-31,3.
