The model used multiple stepwise regression method and back propagation method independently.
模型分别采用多元逐步回归方法和反向传播方法。
The following paper constructs a artificial neural network - named water quantity predicting model, using automatically adapting and step-self-changing back propagation method(ABPM).
采用自适应变步长的后向传播算法（ABPM）构建了一个人工神经网络用水量预测模型。
The method and steps of BP (Back Propagation) neural network for recognizing and forecasting power load in batch data processing of chronological sequence is presented.
介绍了在批量处理时间序列情况下，BP神经网络辨识预测电力负荷的方法和步骤。
Data of ultimate shear stress of hyper concentration flow are trained several times by Back Propagation (BP) neural network method.
应用误差逆传播（BP）神经网络方法，对高含沙流体极限剪应力进行了多次训练。
Aiming at there is long delay of TCP data such as control command etc in remote experiment network, a video transmission control method is presented based on Back Propagation (BP) neural network.
在远程实验网络中，控制命令等TCP数据会出现较大延迟。为此，提出一种基于BP神经网络的视频传输控制方法。
The essence of back propagation networks is that make the change of weights become little by gradient descent method and finally attain the minimal error.
其实质是采用梯度下降法使权值的改变总是朝着误差变小的方向改进，最终达到最小误差。
Based on the linearization approximation, nonlinear schrodinger equation is quantized, the influences of the soliton source chirp on quantum soliton is studied by using the back-propagation method.
在线性近似条件下，量子化了非线性薛定谔方程，用后向传播法数值求解了孤子源啁啾对量子光孤子的影响。
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。
A method to predict the wood radial thermal conductivity based on back propagation (BP) neural network model which has non-linear relation highly was proposed.
利用神经网络所具有的输入-输出之间的高度非线性映射关系，给出一种利用BP神经网络模型预测木材径向导热系数的方法。
Its learning rule is to use the steepest descent method, by back-propagation network to continuously adjust the weights and thresholds, so the network and the minimum sum of squared errors.
它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。
On the basis of molecular subgraph coding method, a back propagation neural network was trained on the molecular subgraph code to predict Gibbs energy of alkanes.
采用分子子图编码法将烷烃的分子子图码作为人工神经网络的输入参数 ，对烷烃的吉布斯自由能进行预测 。
On the basis of molecular subgraph coding method, a back propagation neural network was trained on the molecular subgraph code to predict Gibbs energy of alkanes.
采用分子子图编码法将烷烃的分子子图码作为人工神经网络的输入参数 ，对烷烃的吉布斯自由能进行预测 。
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