【作者】 陈泰任； 曹卫华； 吴敏； 雷琪；

【Author】 Chen Tairen,Cao Weihua,Wu Min,Lei Qi School of Information Science and Engineering,Central South University,Changsha 410083,P.R.China

【机构】 中南大学信息科学与工程学院；

【摘要】 本文在分析焦炉火道温度特性的基础上,提出了一种将基于时间差分法(TD)的Elman神经网络(TD-ENN)和基于线性回归(LR)的Elman神经网络(LR-ENN)专家集成的高精度焦炉火道温度软测量模型。首先,利用蓄顶温度和立火道温度的关系,分别建立了一元、二元和十二元LR模型,并采用Elman神经网络将三个模型的输出进行融合,通过比较证明该集成方法的有效性;利用基于时间差分法(TD)的Elman网络对LR-ENN模型的误差进行学习和多步预测;最后,采用专家经验将这两者进行集成,从而获得火道温度软测量值。实际运行结果验证了该集成模型的有效性。更多还原

【Abstract】 Based on the features of coke oven flue temperature,a new integrated model combining temporal difference method (TD),linear regress(LR) and elman neural network (ENN) is proposed.Firstly,LR models with one variable,two variables and twelve variables are built base on the relationship between the flue temperature and top of regenerators’ tem- perature,and rationally integrated by elman neural network (LR-ENN).Comparing to the unique LR models,the integrated model shows the good performance.Then modified elman neural network model based on the temporal difference method is used(TD-ENN).Through this model,the error of the LR-ENN is predicted multi-step ahead.At last,the flue temperature is get through the expert coordinator which is used to coordinate the outputs of LR-ENN and TD-ENN.The actual results con- firm the integrated model’s validity.更多还原