Applying Artificial Neural Network Model on Investigating the Fiber Diameter of Polybutylene Terephthalate (PBT) Spunbonding Nonwovens: Comparison with Mathematical Statistical Method

摘要：

In this paper, two models are founded and introduced to predict the fiber diameter of polybutylene terephthalate spunbonding nonwovens from the spunbonding process parameters. The results indicate the artificial neural network model has good approximation capability and fast convergence rate, and it can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the mathematical statistical method. This area of research has great potential in the field of computer assisted design in spunbonding technology.

关键词： spunbonding nonwoven polybutylene terephthalate fiber diameter mathematical statistical method artificial neural network model

作者: B.Zhao

作者单位: College of Textiles,Zhongyuan University of Technology,Henan,Zhengzhou,450007,China

会议类型: 国际会议

会议名称: The 3rd Conference of Cross-Strait Engineering Education and Ceeusro & 1st International Conference on Engineering Technologies and Ceeusro(ICETC2009)(第三届工程技术与产学研研讨会暨第一届国际功能制造技术学术会议)

会议地点: 常州

会议语种:英文

页码: 692-696

在线出版日期: 2009-11-19（万方平台首次上网日期，不代表论文的发表时间）