Then some defects such as slow convergence rate and getting into local minimum in BP algorithm are pointed out, and the root of the defects is presented.
分析了BP算法的基本原理，指出了BP算法具有收敛速度慢、易陷入局部极小点等缺陷以及这些缺陷产生的根源。
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。
In the individual credit evaluation part, it quantifies all kinds of scattered data, and to improve BP algorithm it USES local self-adaptive study rate algorithm.
在个人信用评估部分中，对所有的离散数据进行量化处理，然后使用局部学习率自适应算法，对BP算法加以改进。
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。
The algorithm can get global minimum easily with a wide variety of functions of hidden neurons, and no problems such as local minima and slow rate of convergence are suffered like BP algorithm.
新算法选择很广一类的隐层神经元函数，可以直接求得全局最小点，不存在BP算法的局部极小、收敛速度慢等问题。
The particle swarm optimization(PSO) algorithm, is used to train neural network to solve the drawbacks of BP algorithms which is local minimum and slow convergence.
针对多层前馈网络的误差反传算法存在的收敛速度慢，且易陷入局部极小的缺点，提出了采用微粒群算法（PSO）训练多层前馈网络权值的方法。
Chaotic mechanism is introduced to normal BP algorithm, and the problem of local limit value for network is solved using global moving characteristic of chaotic mechanism is weight optimization.
将混沌机制引入常规BP算法，利用混沌机制固有的全局游动，逃出权值优化过程中存在的局部极小点，解决了网络训练易陷入局部极小点的问题。
And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.
且改进的粒子群算法在模糊神经网络权值的训练中收敛速度和跳出局部最优的能力都要比BP算法更优。
Improving BP neural network with simulated annealing algorithm can overcome the defect of falling into local optimal point easily, and further improve the network performance.
用模拟退火算法改进BP神经网络，克服了BP神经网络极易陷入局部最优点的缺点，进一步提高了网络的性能。
Since BP algorithm has the defect that the speed of constriction is slow and have local extreme data, two kinds of improvement was put forward.
针对BP算法的收敛速度慢和局部极值的缺点，提出了两种改进方法。
The hybrid algorithm based on GA and BP algorithm has both rapid local searching ability derived from BP and better global searching ability derived from GA.
构建了一种基于GA -BP的混合遗传算法来综合遗传算法的全局优化能力和BP神经网络的快速收敛能力。
Then some defects such as slow convergence rate and getting into local minimum in BP algorithm are pointed out, and the root of the defects is presented.
针对前向神经网络BP算法由于初始权值选择不当而陷入局部极小点这一缺陷，提出新的全局优化训练算法。
Applying improved BP algorithm, it shows the improved BP algorithm can easily converge into the local minimum point and it can improve the accuracy of model.
建模实践表明，改进后的BP算法可能使网络误差函数达到局部极小点，提高了算法的拟合精度。
People put forward radial basis function networks considering the conventional BP algorithm problems of slow convergence speed and easily getting into local dinky value.
对于传统BP算法存在的收敛速度慢和易陷入局部极小值问题，人们提出了径向基函数网络。
In this paper, fuzzy neural network was studied and fuzzy reasoning was realized by use of neural networks structure. BP algorithm is used to optimize local parameter.
本文研究了模糊神经网络，用神经网络结构进行模糊推理，用BP算法调节和优化具有局部性的参数。
A modified BP algorithm of neural network, random adjustment of parameters (RMBP) algorithm, is proposed to overcome the defect of easy going into local minimum of BP neural network.
针对BP(反向传播)神经网络学习易陷入局部极小的缺陷，提出了一种改进BP神经网络学习算法——RMBP算法。
The algorithm solved the problems of the conventional BP algorithm such as converging slowly and falling into the local minimum point easily.
该算法克服了传统BP算法的收敛速度慢，易陷入局部最小点的问题。
The algorithm solved the problems of the conventional BP algorithm such as converging slowly and falling into the local minimum point easily.
该算法克服了传统BP算法的收敛速度慢，易陷入局部最小点的问题。
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