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
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;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2010 International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-8094-4
DOI :
10.1109/ISCID.2010.111