This paper puts forward the ways of reliability prediction based on artificial neural networks, builds the three layers BP neural networks model, and presents its arithmetic in detail.

本文提出了基于人工神经网络的可靠性预测方法，建立了用于数控机床可靠性预测的三层BP神经网络模型，给出了具体的算法。

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Owing to the complicated variable rule of CMMs geometry error, it's difficult to convergence for using common BP neural network model arithmetic with a slow velocity.

由于坐标测量机几何误差变化规律复杂，采用一般的BP神经网络模型算法，速度慢且难以收敛。

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This paper proposed the model of BP neural network and its idiographic arithmetic, then applied it into the discrimination of the water source in mine.

利用BP算法对训练样本进行学习，确定判别模型，根据已训练好的神经网络对样本进行判别。结果表明，采用人工神经网络对矿井水源进行判别，能得到较好的结果。

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