Temperature prediction model of Rotary kiln firing zone Based on Improved BP Neural Network

摘要：

The temperature of the burning zone in the acquisition process is not stable and has an important impact on the quality of pellet. In order to improve the burning zone temperature stability, zone of combustion temperature prediction model is proposed based on the improved BP neural network. According to the field data characteristics, using cluster analysis method for data processing in order to reduce the prediction of interference, the results show that the improved algorithm of the model can overcome the standard BP network algorithm parameter optimization problems, and have better forecasting effect which has important significance to improve the rotary kiln burning zone temperature control precision.

关键词： Rotary kiln Temperature prediction Genetic algorithm BP neural network1

作者: ZhangYong ZhuJing WangLeiming

作者单位: School of Electronic and Information Engineering, Liaoning University of Science and TechnologyAnsha School of Electronic and Information Engineering, Liaoning University of Science and Technology Ansh

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System Design and Engineering Applications(2012年智能系统设计与工程应用国际会议 ISDEA 2012)

会议地点: 三亚

会议语种:英文

页码: 549-552

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）