|本期目录/Table of Contents|

[1]李翔,顾宗栋,薛元,等.基于两种BP神经网络的精纺毛纱性能预测模型的比较[J].浙江理工大学学报,2011,28(03):347-350.
 LI Xiang,GU Zong dong,XUE Yuan,et al. Comparison of Prediction Models of Worsted Yarns Performances Based on Two Kinds of BP Neural Network[J].Journal of Zhejiang Sci-Tech University,2011,28(03):347-350.
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基于两种BP神经网络的精纺毛纱性能预测模型的比较()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第28卷
期数:
2011年03期
页码:
347-350
栏目:
纺织与服装工程
出版日期:
2011-06-30

文章信息/Info

Title:
 Comparison of Prediction Models of Worsted Yarns Performances Based on Two Kinds of BP Neural Network
文章编号:
16733851 (2011) 03034704
作者:
李翔1 顾宗栋2 薛元3 胡国樑1
 1. 浙江理工大学材料与纺织学院, 杭州 310018; 2. 浙江凌龙纺织有限公司, 浙江 嘉善 314104; 3. 嘉兴学院服装与艺术设计学院, 浙江 嘉兴 314001
Author(s):
 LI Xiang1 GU Zongdong2 XUE Yuan3 HU Guoliang1
 1. School of Materials and Textiles, Zhejiang SciTech University, Hangzhou 310018, China; 
2. Zhejiang Linglong Textile Co. Ltd., Jiashan, 314104, China; 
3. School of Garment and Art design, Jiaxing University, Jiaxing 314001, China
关键词:
 BP神经网络 精纺毛纱 单隐层 双隐层
分类号:
TS104.1
文献标志码:
A
摘要:
    在较大输入层样本数、较多输入层节点数的条件下,尝试使用单隐层BP神经网络模型与双隐层BP神经网络模型分别对精纺毛纱的条干不匀率与断裂强力进行预测,分析比较单、双隐层模型的预测性能。结果表明:隐含层节点数为9的双隐层BP神经网络模型预测性能最佳,相关系数值为0.9205;对精纺纱的断裂强力进行预测时,隐含层节点数为8的双隐层BP神经网络模型预测性能最好,相关系数值为0.9171。因此,在输入层样本数较大、输入层节点数较多的条件下,双隐层BP神经网络模型更适合对精纺毛纱的性能进行预测。

参考文献/References:

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备注/Memo

备注/Memo:
 收稿日期: 2010-07-05
基金项目: 浙江省重大科技专项(2008C010693)
作者简介: 李翔(1985-),男,福建宁德人,硕士研究生,主要从事纺织材料的结构与性能研究。
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