| 基于灰色系统理论及RBF神经网络的棉织物透湿性能预测 |
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| 引用本文： | 王健. 基于灰色系统理论及RBF神经网络的棉织物透湿性能预测[J]. 纺织科技进展, 2007, 0(3): 40-42 |
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| 作者姓名： | 王健 |
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| 作者单位： | 安徽农业大学,轻纺工程与艺术学院,安徽,合肥230036 |
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| 摘 要： | 通过测试棉织物的结构参数与透湿性能，应用灰色系统理论计算了棉织物结构参数与透湿量的关联度，并对其排序，结果表明影响棉织物透湿性能的3个主要结构参数依次为孔隙率、纬向紧度和总紧度。利用MATLAB软件，建立了织物透湿性能的RBF神经网络预测模型，用此模型预测棉织物的透湿性能具有运算速度快、精度高和泛化能力强的特点。
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| 关 键 词： | 棉织物 透湿性能 孔隙率 紧度 灰色关联 RBF神经网络 |
| 文章编号： | 1673-0356（2007）03-0040-03 |
| 修稿时间： | 2007-03-23 |
The prediction of cotton fabric moisture permeability based on grey system theory and RBF neural network |
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| WANG Jian. The prediction of cotton fabric moisture permeability based on grey system theory and RBF neural network[J]. Progress in Textile Science & Technology, 2007, 0(3): 40-42 |
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| Authors: | WANG Jian |
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| Affiliation: | Light--Textile Engineering and Art College, Anhui Agricultural University, Hefei 230036,China |
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| Abstract: | Correlation degree between stuctural parameters and moisture penetrate quantity was calculated by testing structural parameters and moisture permeability of cotton fabrics and using grey system principle, and the order of the result was proposed. The result showed that the most important structure parameters were porosity,weft tightness and total tightness in order. The RBF neural network model of cotton fabric porosity was built with MATLAB soft. The result showed the RBF neural network model mentioned in this paper has fast computing speed and high precision and good generalization capacity. |
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| Keywords: | cotton fabric moisture permeability porosity tightness grey incidence analysis RBF neural network model |
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