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Prediction of networked control system time-delay based on grey model and Elman neural network

机译:基于灰色模型和Elman神经网络的网络控制系统时延预测

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摘要

In order to improve the time-delay prediction accuracy, this paper proposes a network time-delay prediction method based on grey model and Elman neural network. Grey model can weaken the randomness of the time-delay sequence, and the Elman neural network has good prediction ability for nonlinear sequence. The advantages of these two methods are combined. The final predictive time-delay is obtained by grey model and Elman neural network multiplied by their weighting coefficients. The optimal model weighting coefficients are determined by principle of minimum variance. The simulation results show that this combination prediction method has higher prediction accuracy with smaller predictive error.
机译:为了提高时延预测精度,提出了一种基于灰色模型和Elman神经网络的时延预测方法。灰色模型可以减弱时延序列的随机性,Elman神经网络对非线性序列具有良好的预测能力。结合了这两种方法的优点。通过灰色模型和Elman神经网络乘以它们的权重系数,可以得到最终的预测时延。最佳模型加权系数由最小方差原理确定。仿真结果表明,该组合预测方法具有较高的预测精度和较小的预测误差。

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