bp neural network calibration bp神经网络标定
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。
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