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。
A new method ameliorating the calibration accuracy for flowmeter that is based on BP network - (genetic) algorithms (GA) is proposed.
提出一种基于神经网络(BP)-遗传算法(GA)的高精度流量仪表标定方法。
The experiment results indicate that the improved BP network model can avoid nonlinear modeling and enhance the calibration precision and the flexibility, which has real significance.
结果表明：采用改进的BP神经网络能够避免对摄像机进行非线性建模，有利于提高标定精度，增加系统的灵活性，更具有实际意义。
BP artificial neural network was used to establish the calibration model of subjects' total cholesterol, glucose and hemoglobin values against dynamic spectrum data.
利用BP神经网络对此样本的总胆固醇、血糖、血红蛋白进行了建模和预测。
BP artificial neural network was used to establish the calibration model of subjects' total cholesterol, glucose and hemoglobin values against dynamic spectrum data.
利用BP神经网络对此样本的总胆固醇、血糖、血红蛋白进行了建模和预测。
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