为了实现制浆蒸煮终点的精确预测，建立了基于广义回归神经网络(GRNN)的预测模型。

A model based on general regression neural networks (GRNN) has been established to predict the end point of batch pulping cooking.

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针对诊断传感器偏置故障与漂移故障的难点问题，提出了一种基于广义回归神经网络(GRNN)的传感器故障诊断方法。

Aimed at solving the challenging problem of diagnosis for sensor bias and drift faults, a novel approach of sensor fault diagnosis based on generalized regression neural network (GRNN) is proposed.

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介绍了径向基函数网络的函数逼近原理和方法，提出了一种基于广义回归神经网络（GRNN）的传感器非线性误差校正方法。

The RBF network function approximation theory and method are introduced, and the method of nonlinear error correction of sensor is presented based on generalized regression neural network(GRNN).

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介绍了径向基函数网络的函数逼近原理和方法，提出了一种基于广义回归神经网络（GRNN）的传感器非线性误差校正方法。

The RBF network function approximation theory and method are introduced, and the method of nonlinear error correction of sensor is presented based on generalized regression neural network(GRNN).

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