Research on State Prediction of Flue Gas Turbine Based on Elman Neural Network

摘要：

In the light of the characteristics of Elman neural network model which can be approximate to the arbitrary non-linear function and its ability to reflect the dynamic characteristics of the system,this paper provides a state prediction model of flue gas turbine by applying Elman neural network and makes prediction of the overall vibration value. Compared to traditional static BP network prediction model,examples show that Elman neural network model has simple structure and wonderful dynamic characteristics. This model can accurately predict the state of flue gas turbine,with high convergence rate and precision. It has a good performance in nonlinear time series prediction,indicating that this model is feasible in the state prediction of flue gas turbine.

关键词： Elman Neural Network Flue Gas Turbine State Prediction

作者: Chen Tao Xu Xiaoli Wang Shaohong

作者单位: Beijing Institute of Technology,Beijing,China,100081 Beijing Institute of Technology,Beijing,China,100081 Beijing Information Science & Technology Univer

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 3145-3148

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）