DocumentCode
2183042
Title
Application of BP Neural Networks on Prediction of Operating Condition of Loom
Author
Zhu, Yanhong ; He, Dongbin ; Duan, Liying
Author_Institution
Shijiazhuang Posts & Telecommun. Tech. Coll., Shijiazhuang, China
Volume
2
fYear
2010
fDate
29-31 Oct. 2010
Firstpage
91
Lastpage
94
Abstract
In order to forecast quickly the operating condition of the loom, optimize the parameters of loom production, so that the production efficiency of loom will be improved. This paper studies the prediction of the operating condition of the loom based on the neural networks. The neural networks technology is applied to forecast the operating condition of the loom production, establishes corresponding prediction model of loom production. With the help of neural networks samples are trained and checked, then are applied to forecast the operating condition of the loom production, the results are compared with the Bayesian theorem. The study indicates that network model based on the neural networks has reliability and high accuracy.
Keywords
Bayes methods; backpropagation; neural nets; production equipment; BP neural networks; Bayesian theorem; loom operating condition prediction; loom production efficiency; BP neural network; bayesian theorem; prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2010 International Symposium on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-8094-4
Type
conf
DOI
10.1109/ISCID.2010.111
Filename
5692741
Link To Document