反向传播

方法：应用反向传播神经网络（BP神经网络）模型。

Method : A back propagation neural networks was used .

对人工神经网络，详细推导了误差反向传播（BP）算法，并对几种改进的BP算法作了介绍。

The back propagation neural networks were particularly constructed .

神经网络反向传播模型用于CmI的能级分类

Classification of Cm_ ⅰ Energy Levels Using the Back-propagation Neural Network

神经网络采用带有动量项和自适应学习率的反向传播算法（BP）进行训练。

The system adopts back-propagation learning algorithm with momentum .

3）在神经网络中采用了BP（反向传播）算法。

3 ) Select BP ( Back - Propagation ) algorithm in nerve network .

最后利用反向传播（BP）神经网络进行纹理的分类识别。

The texture classification is completed with back propagation ( BP ) neural network .

使用自适应谐振理论（ART）和误差反向传播（B）两种神经网络，开发了汽轮发电机组振动故障诊断模型。

The vibrating fault diagnosis system for turbo-generator unit based on ART and BP network is developed in this work .

神经网络的BP（误差反向传播）学习不法是针对多层前债结构的神经网络进行研究而·提出的一种有效的学习算法。

The back propagation ( BP ) learning algorithm of Artificial Neural Net was briefly reviewed .

探讨了利用反向传播神经网络和BP算法确定市场响应函数的方法。

This paper discusses backpropagation neural network model and BP algorithm to determine market response functions .

本文中人工神经网络模型主要是BP反向传播误差算法。

In this article the nerve network model mainly is the BP reverse propagated error algorithm .

提出了反向传播人工神经网络（BPANN）参数学习的模拟退火回火算法。

An annealing backfire algorithm to get the parameters of BP ANN was presented .

基于误差反向传播算法的OFDM系统频域均衡

Frequency-domain Equalization in OFDM System Based on the BP Algorithm

研究确立了反向传播BP模型在测算人员编制中的应用方法及技术路线。

The method and technical route of the B P model applied to estimate personnel establishment is established .

在本文中将我们改进的圆形反向传播网络模型（ImprovedCircularBackPropagation&ICBP）应用于时间序列预测，进行了单步和多步时间序列预测研究。

In this article , we applied our improved circular back-propagation ( ICBP ) network to single step and multi-steps time series prediction respectively .

参数辨识中，采用了反向传播学习算法（即BP算法）。

BP ( back propagation ) algorithm has been employed for the parameter identification of the fuzzy neural network .

研究了在确定了结构损伤区域的条件下，应用反向传播（BP）神经网络同时实现对具体损伤构件及其损伤程度识别的方法。

A method for identifying the damaged member and damage extent simultaneously by a back-propagation neural network is investigated .

最后利用前馈神经网络的误差反向传播模型（BP）网络的外延和信息表达能力解决了非储层的定量识别。

And the extrapolation and information expressivity of BP network is a great help in quantitative identification for non-reservoir .

基于反向传播神经网络模型（BP）建立了3层网络系统用于处理织物风格信号。

Based on the Back-Propagation neural network model , a three-layer network system is established to process fabric handle signals .

对刘国东等提出的BP（误差反向传播）神经网络归一化模型进行了改进，得到了适合钢轨交流闪光焊落锤质量预测的BP神经网络归一化模型。

An improved back propagation ( BP ) neural networks model was proposed based on the presented by Liu Guo-dong .

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。

This research built a flight phase safety risk assessment model basing on Back Propagation ( BP ) neural network .

用反向传播神经网络求解J积分

A method for calculating J-integral through neural networks

结合多层前馈式反向传播（BackPropagation&BP）神经网络，建立了基于腐蚀形貌特征的腐蚀诊断方法。

A new method for corrosion type identification and corrosion rate prediction is developed based on the corrosion characteristics extraction combining with Back Propagation ( BP ) neural networks .

反向传播这一算法把支持delta规则的分析扩展到了带有隐藏节点的神经网络。

Back-propagation is an algorithm that extends the analysis that underpins the delta rule to neural nets with hidden nodes .

选用反向传播神经网络模型（BP网络），网络识别所需要的特征参数能够反映木材缺陷的全部特征。

Back propagation networks was used to recognize all the characteristic parameters , which can reflect all the characteristics of wood defects .

BP神经网络作为一种基于误差反向传播的多层前向网络，最主要的特性是具有非线性映射功能，可以逼近任意的非线性函数。

As the most important characteristic of BP neural network is the nonlinear mapping function , it can approximate any nonlinear function .

首先研究了将改进遗传算法和误差反向传播（BP）算法相结合的混合算法来训练人工神经网络。

The application of hybrid algorithm which combines improved genetic algorithm and error back-propagation algorithm in artificial neural network training is studied first .

介绍了人工神经网络（ANN）的主要特点及误差反向传播网络（BP）的工作原理。

Main characteristics of Artificial Neural Network ( ANN ) and the principle of back-propagation algorithm ( BP ) were introduced .

这一训练方法被称之为HMM的反向传播训练方法。

This approach to the training of HMM is called back propagation training approach .

最后，本文采用了基于反向传播算法（BP算法）的神经网络系统来识别字符，其优点是结构设计简单，自学习能力较强，识别速度快。

Last the article make the network with BP Algorithm to recognize the character , the strongpoint is great self-studying ability and fast speed .

利用误差反向传播（BP）人工神经网络，建立了海域船舶溢油风险程度甄别的评价模型。

An artificial neural network is made to identify the oil spill risk degree of the different sub-areas of a sea area being interested .