A method based on recurrent neural network compensation Kalman's evaluation error is proposed in order to enhance the evaluation precision.
为了提高卡尔曼滤波估计精度，提出了一种基于回归神经网络补偿卡尔曼滤波器估计误差的方法。
Each subsystem is designed using adaptive control with neural network compensation. The stability of the system is guaranteed by the proposed parameter and weight turning law.
各控制子系统的设计采用自适应控制和神经网络相结合的方法，所提出的参数和权重的自适应调整律保证系统的稳定性。
It is the first time that a converting furnace endpoint prediction model based on an improved BP neural network and error compensation of linear regression.
提出了基于改进的BP神经网络学习算法和自适应残差补偿算法的炼铜转炉吹炼终点组合预报模型。
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