小波模糊神经网络在高炉炉温预测中的应用  

The Application of Wavelet Fuzzy Neural Network in BF Temperature Prediction

作　　者：路永辉[1] 马翠红[1] 

机构地区：[1]河北理工大学

出　　处：《安徽冶金》2008年第4期24-26,共3页Anhui Metallurgy

摘　　要：在运用模糊神经网络进行预测的基础上,建立了一种应用小波理论对时间信号进行去噪,根据去噪处理对模糊神经网络作相应处理的预测模型,并将所建模型应用于高炉炉温预测。仿真结果证明小波模糊神经网络比模糊神经网络更具优越性,预测准确率明显提高。Based on prediction by fuzzy neural network, a prediction model is established by using wavelet theory to denoise time signal and then treating fuzzy neural network according to the denoising result. This model has been applied to blast furnace temperature prediction, showing that this method is significantly more accurate than fuzzy neural network.

关 键 词：小波理论 模糊神经网络 高炉炉温 铁水硅含量 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] V241.507[自动化与计算机技术—计算机科学与技术]