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A Worsted Yarn Virtual Production System Based on BP Neural Network
作者姓名:董奎勇  于伟东
作者单位:CollegeofTextiles,DonghuaUniversity,Shanghai,200051
基金项目:SupportedbytheTechnicalInnovationProjectoftheStateEconomicandTradeCommission (0 2CJ 14 0 5 0 1)
摘    要:Back-Propagation (BP) neural network and its modified algorlthm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qua/ides. The results from these two series of models have been compared with the measured values respectively, proving that the accuracy in both the prediction model and the deduction model is high. The experimental results and the corresponding analysis show that the BP neural network is an efficient technique for the quality prediction and has wide prospect in the application of worsted yam production system.

关 键 词:BP神经网络  精纺工艺  虚拟生产系统  纱线性能  质量  羊毛纺织

A Worsted Yarn Virtual Production System Based on BP Neural Network
DONG Kui-yong,YU Wei-dong College of Textiles,Donghua University,Shanghai.A Worsted Yarn Virtual Production System Based on BP Neural Network[J].Journal of Donghua University,2004,21(4):34-37.
Authors:DONG Kui-yong  YU Wei-dong College of Textiles  Donghua University  Shanghai
Institution:College of Textiles,Donghua University,Shanghai,200051
Abstract:Back-Propagation (BP) neural network and its modified algorithm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qualities. The results from these two series of models have been compared with the measured values respectively, proving that the accuracy in both the prediction model and the deduction model is high. The experimental results and the corresponding analysis show that the BP neural network is an efficient technique for the quality prediction and has wide prospect in the application of worsted yarn production system.
Keywords:BP neural network  yarn properties  top qualities  virtual production  prediction  deduction  
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