The modified algorithm of BP network is introduced.
介绍了BP网络的改进算法。
LM learning algorithm is adopted in BP network learning.
BP网络的学习采用了LM学习算法。
That BP network used for predicting quality of wire bonding is feasible and valid.
BP网络用于金丝键合质量的预报具有可行性和有效性。
The NN learning block, using BP network, is determined by comparing the simulation results.
神经网络学习模块采用BP网络，通过仿真分析确定了网络的结构。
Based on BP network, the example of nonlinear regression by artificial neural networks is given.
以BP网络为例给出了基于人工神经网络的非线性回归实例分析。
Methods and steps using the MATLAB neural net tool kit to design BP network are introduced in detail.
文章详细论述了利用MATLAB神经网络工具箱设计BP网络的方法和步骤。
The scale factor training algorithm has been brought forward to accelerate the training of BP network.
提出了比例系数BP网络训练算法，提高了网络的训练速度。
To accelerate the training speed of BP network, a joint-optimized fast BP learning algorithm is proposed.
针对BP网络学习速度的缓慢性，本文提出了一种联合优化后的快速学习算法。
The sale historic data were obtained from data warehouse and the sale trend was forecasted with BP network.
该模型通过数据仓库获取销售历史数据，利用BP网络进行走势预测。
Finally, a new approach (BP Network) to predicting the durability factor of concrete has been proposed here.
最后，本文提出用BP神经网络预测混凝土抗冻耐久性系数的方法。
BP network model of groundwater quality assessment based on the calculation of BP neural network is presented.
阐述了人工神经网络基本原理，介绍了BP网络的地下水水质评价模型。
This paper studies BP network, realizes the method of gradient descent, gets better result than traditional one.
本文研究了BP网络，实现了“梯度下降法”的网络训练方法，获得了较传统方法好的效果。
So adding a penalty term to the error function of BP network is an important approach to gain better generalization.
所以在BP网络的误差函数中加入惩罚项是提高网络泛化能力的一个重要途径。
In this paper we attempt to extend the study of marketing risk pre-warning to include the application of BP network.
基于现存研究成果的局限，本文试图将BP网络运用到企业营销风险预警的研究中。
Compared with traditional BP network, the result indicated that RBF has better accuracy and adaptability of the network.
与传统的BP神经网络模型相比较，结果表明，RBF网络具有更高的精度和更好的泛化能力。
Comparing the predicted data to expectation, the BP network is proved an effective method for predicting unit price of BOQ.
通过比较预测值与期望值，验证BP神经网络方法可以作为预测工程量清单单价的方法。
The inverse mapping is achieved through BP network, and neural network modul is constructed for designing process parameters.
通过误差逆传播(BP)网络实现了逆映射，建立了工艺参数设计的神经网络模块。
A novel control method based on BP network controller is presented for the nonlinearities in active vibration isolation system.
针对主动隔振系统存在的非线性，提出一种基于BP网络控制器的主动控制方法。
Through analyzing the influence factor of profile adjustment, the BP network effect prediction model is established and optimized.
通过对影响调剖效果的因素分析，建立了BP网络效果预测模型并对其进行优化改进。
The results indicate that the application of integrated BP network to the evaluation of municipal groundwater quality is successful.
实例表明，将此网络模型应用于城市地下水水质评价是有效的、可行的。
Based on the explanation on principle of artificial neural network, the BP network model for reservoir operation rules is established.
阐述了人工神经网络的基本原理，提出了建立水库优化调度函数的BP网络模型。
Recent studies on Generalized Congruence Neural Network (GCNN) show that the convergence rate of GCNN is faster than that of BP network.
有关广义同余神经网络（GCNN）的初步研究表明，相对于普通BP网络，GCNN具有很快的收敛速度。
Through error analysis to prove grey related between analysis and BP network is combined to predict magmatic intrusion range is feasible.
通过误差分析证明，将灰色关联分析与BP网络结合起来进行岩浆侵入范围的预测是可行的。
Fuzzy Multi-Factorial evaluation is used in BP Network reduction structure evaluation, which offers a criterion for BP Network structure.
而且把模糊综合评价引入BP网络结构评价，为约简bp网络结构提供评判标准。
The bearing life forecast model based on BP network is researched. The multi step and multi feature forecasts can be realized concurrently.
试图用BP神经网络建立轴承寿命预测模型，并在该模型上进行多特征参数和多步预测方法的研究。
The first network is BP network with one hidden layer, and the second network is linear status Neural network based on linear system dynamic equation.
第一种神经网络是具有一个隐层的动态前向BP网络，第二种是基于线性系统动态方程的线性状态神经网络。
BP network with the strong nonlinearity mapping ability can summarize the rule from acquired data to obtain the inherent laws of these data automatically.
BP网络具有很强的非线性映射能力，能从已有数据中自动地归纳规则，获得这些数据的内在规律。
With improved BP network, Adopting deep, short resistivity, and acoustic logging, the model to recognize oil layer and water flooded layer is established.
利用改进的BP算法，采用深、浅侧向电阻率、声波时差测井建立了油层、水淹层的识别模型。
With improved BP network, Adopting deep, short resistivity, and acoustic logging, the model to recognize oil layer and water flooded layer is established.
利用改进的BP算法，采用深、浅侧向电阻率、声波时差测井建立了油层、水淹层的识别模型。
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