In the research, based on BP neural network theory, a printer calibration model is provided according to sorting experiment data by hue Angle range.

在研究中，利用BP神经网络理论，提出并建立了按色相角范围对实验数据分类的打印机标定模型。

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The result of experiment shows that the developed model has more accuracy than the routine linear regression model and traditional neural network model.

实验结果表明，本文提出的水质反演模型较常规的线性回归模型和传统的神经网络模型有更高的反演精度。

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As the artificial neural network and stepwise regression analysis are respectively applied to the data of crude wax deposition experiment, the model of wax deposition velocity was established.

分别采用人工神经网络法和逐步回归分析法对原油管道蜡沉积实验数据进行分析处理，建立蜡沉积速率模型。

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