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A new Integrated Model and its Application to Soft-sensing of the Flue Temperature in Coke Oven

机译:一种新的集成模型及其在焦炉中烟道温度的软感

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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'' temperature, 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 confirm the integrated model''s validity.
机译:基于焦炉烟道温度的特征,提出了一种结合时间差分方法(TD),线性回归(LR)和ELMAN神经网络(ENN)的新集成模型。首先,具有一个变量的LR模型,两个变量和12个变量是基于烟道温度和再生器的高温之间的关系的基础,由Elman神经网络(LR-ENN)合理整合。与唯一的LR模型相比,集成模型显示出良好的性能。然后使用基于时间差分方法的修改Elman神经网络模型(TD-ENN)。通过该模型,LR-ENN的误差预测了前进的多步。最后,烟道温度通过专家协调员获得,用于协调LR-ENN和TD-ENN的输出。实际结果证实了集成模型的有效性。

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