A new method of prediction on the radiant brightness values of deuterium lamps is proposed using back propagation (b p) neural network.
本文提出了应用B - P神经网络预测氘灯辐亮度值的新方法。
Aim at data inspection and mode identification of atmospheric environment, B-P network evaluation mode was established by the application of artificial neural network theory.
针对大气环境中的数据监测与模式识别问题，应用人工神经网络理论，在自然环境大气腐蚀试验网站建立大气环境质量B - P网络评价模型。
Then, as artificial neural network is better in constructing financial prewarning model than other linear and regression models, a new financial prewarning model based on B-P model was constructed.
然后，利用人工神经网络在建立财务预警模型方面优于其他线性和回归模型的特点，基于B - P模型构建了一个新的混合财务预警模型。
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