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

机译:基于Elman神经网络的燃气轮机状态预测研究。

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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.
机译:鉴于艾尔曼神经网络模型的特征可以近似于任意非线性函数及其反映系统动态特性的能力,本文应用艾尔曼神经网络提供了烟气涡轮机状态预测模型。并预测整体振动值。实例表明,与传统的静态BP网络预测模型相比,Elman神经网络模型具有结构简单,动态特性好等特点。该模型可以准确预测烟气涡轮机的状态,收敛速度快,精度高。在非线性时间序列预测中具有良好的性能,表明该模型在烟气透平状态预测中是可行的。

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