The BP arithmetic of neural network is mainly applied to solve the problems.
主要应用到了神经网络中的BP算法来解决问题的。
The ANN BP arithmetic can solve the problem of nonlinear mathematics effectively, and possess higher collateral processing ability.
人工神经网络BP算法可有效解决非线性数学建模问题，并具有较强的并行处理能力。
Based on the research of the BP arithmetic and RBF arithmetic, the NN training and forecast model which is suitable for the environment-monitoring data is proposed.
通过对BP算法和RBF算法的研究，确定了适合环境监测数据COD值的神经网络训练与预测模型。
The nonlinear function map can be realized with the classic BP arithmetic and the identifying result will be relatively good under the study rule of supervising type.
传统的BP算法可以实现非线性函数的映射，经过有监督式的学习规则可以达到比较好的识别效果。
The nonlinear function map can be realized with the classical BP arithmetic and the identifying result will be relatively good under the study rule of supervising type.
传统的BP算法可以实现非线性函数的映射，经过有监督式的学习规则可以达到比较好的识别效果。
Traverses the BP arithmetic to solve non-linear equations in one variable, presents and proves the convergence theorem of the arithmetic, shows the application example.
遍历BP算法来解决非线性方程的一个变量，提出并证明了该算法的收敛性定理，给出了应用示例。
This paper traverses the BP arithmetic to solve non-linear system in one variable, presents and proves the convergence theorem of the arithmetic, shows the application example.
详细研究了一种一元非线性系统的BP算法，提出并证明了该算法的收敛性定理，给出了该算法的应用实例。
Computer program is written via VB and MATLAB and the recognize system of tanker car is accomplished based on PCA characteristic pick-up and BP nerve network arithmetic.
应用VB和MATLAB编写了计算机程序，形成了基于罐车PC A特征和BP神经网络算法的识别系统。
This paper puts forward the ways of reliability prediction based on artificial neural networks, builds the three layers BP neural networks model, and presents its arithmetic in detail.
本文提出了基于人工神经网络的可靠性预测方法，建立了用于数控机床可靠性预测的三层BP神经网络模型，给出了具体的算法。
Method the artificial neural network and the advanced BP training arithmetic operations based on momentum factor technique are used.
方法采用人工神经网络方法和基于动量因子技术的改进BP网络训练算法。
Owing to the complicated variable rule of CMMs geometry error, it's difficult to convergence for using common BP neural network model arithmetic with a slow velocity.
由于坐标测量机几何误差变化规律复杂，采用一般的BP神经网络模型算法，速度慢且难以收敛。
To compare arithmetic performance, the authors also processed the spectral data with partial least squares and PCA-BP neural network.
为了比较算法的性能，作者又分别采用了偏最小二乘法、主成分分析结合BP神经网络进行数据处理。
Based on error back propagation (BP) arithmetic, many improvements are put forward because of its disadvantages.
在误差反向传播(BP)算法的基础上，针对其不足提出了多种改进算法。
Fuzzy optimal control arithmetic was designed for each module, and an improved BP neural network was introduced to implement the fuzzy relation.
对每个控制模块设计了相应的模糊优化控制算法，并用改进的BP神经网络实现算法的模糊关系。
This paper proposed the model of BP neural network and its idiographic arithmetic, then applied it into the discrimination of the water source in mine.
利用BP算法对训练样本进行学习，确定判别模型，根据已训练好的神经网络对样本进行判别。结果表明，采用人工神经网络对矿井水源进行判别，能得到较好的结果。
In the arithmetic base, besides some general predict algorithm as glide average, exponential smoothness, linearity regress, etc, it adds BP neural network algorithm for forecast.
在算法库中，除了部分的常规预测算法，如滑动平均、指数平滑、线性回归等，还加入了BP神经网络算法进行预测。
BP neural network arithmetic is used in the handwritten numeral recognition system. In order to reflect the whole character, we use many input modes to train the networks.
将BP神经网络引入到手写数字识别中，并采用多种输入模式对不同的BP网络进行训练，从而达到全面反映数字特征的目的。
BP neural network arithmetic is used in the handwritten numeral recognition system. In order to reflect the whole character, we use many input modes to train the networks.
将BP神经网络引入到手写数字识别中，并采用多种输入模式对不同的BP网络进行训练，从而达到全面反映数字特征的目的。
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