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。
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。
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。
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。
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。
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。
This paper deals with the structural health detection using measured frequency response functions (FRFs) as input data toa back propagation (BP) artificial neural networks (ANNs).
研究将实测结构频率响应函数作为反向传递人工神经网络的输入数据，用来进行结构健康检测。
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。
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。
Chapter two describes the basic knowledge of ANN and BP (Error Back Propagation), and how to use in MATLAB.
第二章介绍了神经网络和BP网络的基础知识，及在MATLAB中的应用方法。
By means of BP (error back propagation) artificial nerve network, with data from alarm, weather and engineering documents, microwave hop performance analysis and forecast model is established.
利用神经网络的误差反向传播算法(BP算法)，结合告警、天气和工程设计几方面的数据资料建立了微波中继段告警分析预测模型。
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。
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。
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。
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。
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。
The learning algorithm is BP (Back Propagation) algorithm.
学习算法为反向传播算法。
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。
Based on the idea of standard back-propagation (BP) learning algorithm, an improved BP learning algorithm is presented.
在标准反向传播神经网络算法的基础上，提出了一种改进的反向传播神经网络算法。
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。
Based on the BP (back propagation) model for excitation characteristics of transformer, a modified BP model is presented and the corresponding algorithm is also deduced.
在变压器励磁特性的BP模型基础上，提出了一种修正的BP模型，并推导了相应的算法。
Meanwhile, the back propagation learning algorithm is given based on BP.
文章还推导了基于BP的反传学习算法。
Regular back-propagation networks (BP) are fully connected globalized neural networks, it is usually difficult for them to approximate illbehaved systems, which exist in any application field.
常规的反向传播网络（BP）是一种内部呈完全联结的全局性网络，它对非平滑系统的学习能力较弱。
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。
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。
应用推荐