• The modified algorithm of BP network is introduced.

    介绍了BP网络的改进算法。

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  • The improved BP network training method was introduced.

    介绍了改进的BP网络训练算法。

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  • LM learning algorithm is adopted in BP network learning.

    BP网络的学习采用了LM学习算法。

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  • Analyze the character, structure and limitation of BP network.

    分析了BP网络的特点、结构及本身的局限。

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  • Then, use a large number of numeral pattern to train BP network.

    然后,使用大量数字样本对BP网络进行训练。

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  • BP network train sample mode analyse the income by finite element model.

    BP网络训练样本由有限元模型模态分析所得。

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  • 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。

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  • 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。

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  • The BP network of forward type have the very strong mode identification and classific ability.

    前馈型BP网络具有极强的模式识别和分类能力。

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  • 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。

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  • The structure revise and optimization calculation has been made to secondary decelerator BP network.

    对二级减速器BP网络模型进行了结构修正与优化计算。

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  • 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。

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  • 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。

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  • We successfully apply BP network in noise cancelling. The effect of practical application is satisfactory.

    本文采用BP网络实现自适应噪声相消,实际应用效果是良好的。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

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  • 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。

    youdao

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