Application of BP Neural Networks on Prediction of Operating Condition of Loom

摘要：

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.

关键词： bayesian theorem BP neural network prediction

作者: Yanhong Zhu Dongbin He Liying Duan

作者单位: Department of Computer Shijiazhuang Posts and Telecommunications Technical College Department of Computer Shijiazhuang University Shiiiazhuang, China

会议类型: 国际会议

会议名称: 2010 International Symposium on Computational Intelligence and Edsign(第三届计算智能与设计国际学术研讨会 ISCID 2010)

会议地点: 杭州

会议语种:英文

页码: 91-94

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）