摘要
文章中将LM算法引入BP神经网络,结合混沌算法和BP神经网络的优势,对于脱硫系统PH值预测(SO2浓度检测)过程来说,详细分析了网络的设计过程,并在MATLAB2011环境下进行编程实现,取得了良好的结果。研究表明,将改进算法的神经网络预测方法运用到脱硫系统进行PH值预测具备可行性,这种网络不但训练速度较快,而且具备较高的预测精度。
In this paper,the LM algorithm is introduced into the BP neural network.PH value of desulfurization system is predicted with the combination of chaos algorithm and the advantages of BP neural network.Design of the network is analyzed in detail and programmed in the MATLAB2011 with good results.The research shows that neural network prediction method with improved algorithm is applied to predict PH value of desulfurization system,which is feasible,faster and with higher accuracy.
出处
《通信电源技术》
2016年第3期117-118,共2页
Telecom Power Technology
关键词
LM算法
SO2浓度预测
湿式脱硫法
神经网络建模
LM algorithm
SO2concentration prediction
wet desulfurization
neural network modeling