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。
With the implicit function relation, BP (Back Propagation) neural network can easily realize the mapping between input data and output data.
通过找出其隐式函数关系，误差反向传播神经网络可以实现输入和输出间的任意映射。
This article introduces a predictive model of Artificial Neural network of red tide biology density and environment factors by use of the back propagation (BP) network.
本文利用人工神经网络中的BP网络，建立赤潮生物密度与环境因子的人工神经网络的预报模型。
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。
The I/O relationship of back propagation algorithm (BP algorithm) for Feed-Forward Multi-layered Neural Network is a mapping relationship, which can resolve the above nonlinear problem.
多层前向神经网络的误差逆传播算法（简称BP算法）的输入输出关系实际上是一种映射关系，适于解决上述非线性映射问题。
High nonlinear problem which is often met in Chemical engineering, taking the study of tray leakage mode as example, is treated by adopted BP (back propagation) algorithm in artificial neural network.
针对化工中经常遇到的高度非线性问题，以塔板研究中的泄漏模型为例，采用人工神经网络中的BP(反向传播)算法进行处理。
To enhance the validity of evaluation, based on ANN(artificial neural network), a comprehensive evaluation model of the safety of road traffic based on BP(back propagation) neural network was built.
为了提高评价的准确性，采用人工神经网络技术，建立了基于BP神经网络的道路交通安全综合评价模型。
Next, an Improved Back Propagation(IBP)algorithm is proposed, considering the drawbacks of the standard Back Propagation (BP) in the neural network theory.
接着，作者对神经网络理论中的标准反向传播算法BP作了改进并提出了IBP算法。
A model for urban road network traffic congestion forecast based on probe vehicle technology, fuzzy logic judgement and back-propagation (BP) neural network was proposed.
提出了一种新的基于移动检测技术、神经网络和模糊判断方法的城市路网动态交通拥挤预测模型。
Combined Genetic Algorithms (ga) and back-propagation neural network (BP), an optimized GA-BP model was established to predict phosphorus content. Some data were chosen to train the network model.
结合遗传算法(GA)和误差反馈型神经网络(BP)，建立了优化的GA - BP神经网络预测模型，预测转炉炼钢过程钢液终点磷含量。
The texture classification is completed with back propagation (BP) neural network.
最后利用反向传播(BP)神经网络进行纹理的分类识别。
Back propagation (BP) algorithm is often used for the weights training of neural network, but the convergence speed of BP algorithm is slow.
反向传播(BP)算法常常用于神经网络的权值训练中，但是BP算法收敛慢。
Objective To study the synthetic process of sodium percarbonate using Back Propagation Artificial Neural Network (BP-ANNS).
目的用前馈(BP)神经网络对过碳酸钠合成工艺进行研究，筛选新的复合稳定剂。
A classical Back Propagation Neural Network (BP NN) has been developed to solve the same problem for comparison.
并应用传统的BP神经网络解决同样的问题以进行比较。
In this paper, the back propagation algorithm of a multilayer feedforward neural network was defined as BP algorithm?
利用前向多层神经网络的反向传播算法，即BP算法。
The potential utility of feed forward artificial neural network using the back propagation algorithm (BP-ANN), in interpreting pyrogram data from traditional Chinese medicine was discussed.
将以误差反向传播为训练算法的前馈式人工神经网络（BP- ANN）首次用于中草药的裂解气相色谱谱图解析。
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。
This research built a flight phase safety risk assessment model basing on Back Propagation(BP) neural network.
基于反向传播（BP）神经网络，建立了民用航空航段安全风险评估模型。
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 trend part of the data can be fitted with BP (back propagation) neural network and the random part is processed by a normal ARMA (auto regressive moving average) model.
采用BP网络对不平稳时间序列进行数据拟合，处理趋势部分，利用ARMA模型处理随机部分。
Principal component analysis (PCA), cluster analysis (CA) and back-propagation artificial neural network (BP-ANN) were used in the data analysis and pattern recognition.
通过主成分分析、聚类分析和BP神经网络对实验数据进行了分析和识别。
The Back Propagation (BP) neural network theory is first used to predict the relation between the data of 1h NMR and 13c NMR.
本文首次将反向传播(BP)神经网络理论应用于13cNMR对1h nmr化学位移值的预测。
The Back Propagation (BP) neural network theory is first used to predict the relation between the data of 1h NMR and 13c NMR.
本文首次将反向传播(BP)神经网络理论应用于13cNMR对1h nmr化学位移值的预测。
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