In this paper, we study the mechanical properties of micro-cantilever beam based on BP network algorithm.
本文将BP网络算法应用在微悬臂梁力学特性的研究中。
Based on expatiated the basic structure model and some general improved algorithms of BP neural network, this paper brings forward a new self-organization learning algorithm.
介绍了BP网络的基本结构模型与常见改进算法，在此基础上提出了一种新型的结构自组织BP网络算法。
A bolt supporting parameter selection neural network construction has been developed, the software is programmed based on BP algorithm.
设计了预测回采巷道锚杆支护参数的神经网络结构，并根据BP算法编制了软件。
The improved BP algorithm added momentum item and chaotic mapping was adopted in fault diagnosis of power supply system based on chaotic neural network.
基于混沌神经网络的供配电系统故障诊断，采用引入动量项和混沌映射的改进BP算法。
A bolt supporting parameter selection neural network construction has been developed, the software is programmed based on BP algorithm. The practice result shows that this method is effective.
设计了预测回采巷道锚杆支护参数的神经网络结构，并根据BP算法编制了软件。实际应用结果表明这一确定锚杆支护参数的方法是有效的。
Finally, the experiment results compared with the BP neural network algorithm and polynomial matching algorithm show that the new model improves color conversion accuracy effectively.
最后，本算法与BP神经网络和多项式拟合算法比较，色彩转换精度有明显提高。
This paper describes a new method for rotor fault diagnosis of electric machinery drag system, artificial neural network, which is based on BP algorithm.
介绍了一种基于BP算法的神经网络在电机转子常见故障诊断中的应用。
For the nonlinear algorithm, we introduce BP neural network into the g.
在非线性算法方面，把神经网络模型引入到g。
In order to correct the measuring results of moisture from microwave resonator, the IA-BP optimization algorithm based evolutionary neural network model is presented.
为了对微波谐振腔含水率测量结果进行校正，提出一种基于IA - BP优化算法的进化神经网络模型。
The theory and algorithm of BP neural network were introduced, and it was used in the fault trend prediction for cutting part transmission system of mining machine.
介绍了BP网络的原理、算法，并用BP网络对采煤机截割部齿轮箱机械传动系统的故障进行了趋势预测。
A scale training algorithm of BP neural network is used, and sample reorganization method is proposed. Its advantage is the fast training speed and good feature extraction ability.
作者使用比例训练的BP算法，提出对训练模式进行样本重组的方法，其特点是训练速度快、特征抽取能力强。
In this paper, we proposed a parallel BP neural network learning algorithm with the support of PC cluster under the circumstance of PVM (parallel Virtual Machine).
本文提出了一种利用微机机群来实现并行处理，在并行编程环境P VM中实现BP神经网络的并行学习算法。
In the arithmetic base, besides some general predict algorithm as glide average, exponential smoothness, linearity regress, etc, it adds BP neural network algorithm for forecast.
在算法库中，除了部分的常规预测算法，如滑动平均、指数平滑、线性回归等，还加入了BP神经网络算法进行预测。
In this paper, an image hashing algorithm based on BP neural network is presented.
本文提出了一种基于BP神经网络的图像哈希算法。
The BP algorithm and the network construction are also discussed.
并讨论了反向传播算法及网络构造。
In this network model, the BP elastic algorithm (RPROP) was adopted and the initialized weight value and valve were optimized and this model has realized the nonlinear.
该网络采用BP弹性算法，同时对初始权值和阀值进行了优化，实现了网络的非线性映射，并有着极快的收敛速度。
Considering the limitation of classical BP algorithm, modified BP algorithm is used to train the network.
考虑到经典BP算法的缺陷，采用改进BP算法对网络进行训练学习。
The modified algorithm of BP network is introduced.
介绍了BP网络的改进算法。
BP algorithm is the most popular training algorithm for feed forward neural network learning. But falling into local minimum and slow convergence are its drawbacks.
BP算法是前馈神经网络训练中应用最多的算法，但其具有收敛慢和陷入局部极值的严重缺点。
Neural network BP training algorithm based on gradient descend technique may lead to entrapment in local optimum so that the network inaccurately classifies input patterns.
基于梯度下降的神经网络训练算法易于陷入局部最小，从而使网络不能对输入模式进行准确分类。
Particle Swarm Optimization as a Swarm Intelligence algorithm, has strong global search capability, can be used for training neural network to overcome the defect of BP algorithm.
然而在粒子群优化算法中，早熟现象时有发生，从而制约了算法的性能。
Aiming at the defects of BP artificial neural network, combined with Differential Evolution Algorithm, the paper proposes a tourist quantity prediction model based on DE-BP neural network.
针对BP人工神经网络所存在的缺陷，结合差异演化算法，提出了基于DE - BP神经网络的旅游客源预测模型。
Aiming at the defects of BP artificial neural network, combined with Differential Evolution Algorithm, the paper proposes a tourist quantity prediction model based on DE-BP neural network.
针对BP人工神经网络所存在的缺陷，结合差异演化算法，提出了基于DE - BP神经网络的旅游客源预测模型。
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