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.
再以广义回归神经网络建立预测模型,与灰预测模型、多元回归模型进行预测能力及报酬率的比较分析。
It is found that it is better to predict the return rate with general regression neural network than with grey prediction and multiple regression model.
再以广义回归神经网络建立预测模型,与灰预测模型、多元回归模型进行预测能力及报酬率的比较分析。
It is found that it is better to predict the return rate with general regression neural network than with grey prediction and multiple regression model.
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