模糊神经网络的学习算法采用的是快速的粒子群优化算法。
A fast stochastic global optimization algorithm, particle group optimization algorithm, was used for training the fuzzy neural network.
此目标函数的优化速度快，大大提高了前馈神经网络的学习效率。
The target function's optimal velocity is high, so it can boost learning efficiency of feed forward neural networks.
研究用微分方程数值解法——线性多步法替代神经网络的学习算法。
Training neural networks by using the linear multi-step method is studied, which is a classical numerical method for differential dynamics.
应用可变斜率的改进的BP算法，极大地加速神经网络的学习速度。
The BP algorithm with the variable slope for the sigmoidal activation function accelerates the ANN training dramatically.
文中定义了肢体运动和体育动作模式匹配的隶属函数，介绍了神经网络的学习方法。
In the paper, the membership functions of limb sports and matching athletic movements are defined, and the study method of neural network is introduced.
利用神经网络的学习能力，BP网的任意非线性映射能力可以模拟这复杂的函数关系。
Such non-linear relation can not be worked out by formula, While BP network can simulate such non-linear relation for its random non-linear mapping ability.
为了避免神经网络的学习过程陷入局部极值点，采用人工免疫网络优化神经网络的参数。
In order to prevent neural network learning from getting into local extreme point, artificial immune network algorithm was used to optimize neural network's parameters.
为有效提高矢量量化码书的性能和学习效率，需进一步改进自组织神经网络的学习算法。
Self-organizing neural network is a very efficient method for pattern recognition and vector quantization(VQ).
在RBF神经网络的学习过程中，根据性能函数调节学习率，可以加快学习的收敛过程。
During the process of learning the RBF neural network, one can accelerate the converging process of learning by regulating the learning speed according to a performance function.
经对性能指标性质的分析给出了一种模糊神经网络的学习算法——二阶段变半径随机搜索法。
Based on the analysis of the performance index a new algorithm, two stage random search algorithm with variable radius, is put forward.
利用神经网络的学习功能对控制器的隶属度函数及推理规则进行修正，以提高其自适应能力。
The membership functions and the inference rules in the controller are modified using the learning functions of neural network so that the adaptability of the controller is further enhanced.
结合小波变换和神经网络的优势给出小波神经网络的结构模型，研究了小波神经网络的学习算法；
Structure model and algorithms of Wavelet Neural Network (WNN) are designed combining the advantages of both wavelet transform and Artificial Neural Network (ANN).
应用模糊控制的逻辑推理性能，借助神经网络的学习能力，提出了一种模糊神经网络预测控制模型。
A fuzzy neural network prediction control model is stated by using the logic inference performance of fuzzy control and the learning ability of neural network.
对此，本文改进了R BF神经网络的学习算法，提出了一种基于聚类的动态自生成隐含层节点的思想。
As for it, by improving learning algorithm of traditional RBF neural network, a new dynamic cluster-based self-generated method for hidden layer nodes is proposed.
整个网络既有神经网络的学习能力，又有模糊系统的基于规则的推理能力，特别是对子类的自动聚类能力。
The whole network has not only the learning ability to neural network, but also the logic ability to fuzzy system based on rules, especially the automatic clustering ability to sub-class.
从本质上讲，人工神经网络的学习过程是一个优化的过程，即根据具体的误差信息来合理地选择网络的权重。
In essence, learning in artificial neural networks is an optimization process, that is, an artificial network adjusts the weights of the network on its concrete error information.
提出的自适应粒子群优化算法，用于优化多层前馈神经网络的拓扑结构，提高了神经网络的学习质量和速度。
The structure of multi-layer feedback forward neural network is optimized by improved PSO. Learning quality and training speed of the neural network are improved.
此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。
In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.
论文提出了一种新的基于互补遗传算子的前馈神经网络三阶段学习方法。该方法把神经网络的学习过程分为三个阶段。
A new mutual genetic operator based three stages feedforward neural network training method is proposed in this paper, which divides neural networks training procedure into three stages.
依据《大学生体育合格标准》，建立起神经网络的学习样本，提出了基于神经网络的的男子大学生身体素质评估的训练模型。
University student physical quality test evaluation model based on neural network was set up (according) to "University student Sports Qualification Standard".
采用人工神经网络的BP算法，以电火花微小孔加工工艺参数正交实验的结果作为神经网络的学习样本，建立电火花微小孔加工多目标工艺参数的预测模型。
Though choosing the experimental results as the learning sample, the performance predictive model of EDM micro-and-small holes is proposed, with the BP algorithm of artificial neural network.
这种类型的学习通常交给神经网络来完成，虽然很难想象，但用决策树来完成这类问题也很简单。
This type of learning could probably be carried out with neural networks, though it is hard to imagine that the problem is simple enough for decision trees.
监督学习是训练神经网络和决策树的最常见技术。
Supervised learning is the most common technique for training neural networks and decision trees.
最近的一些关于神经网络的研究发现：深睡眠对保持头脑清醒以进行第二天的学习非常重要。
Some recent neural network research also indicates that deep sleep may be important in helping clear the brain for new learning the next day.
一个使用这个规则的神经网络称为感知器，并且这个规则被称为感知器学习规则。
A neural net that USES this rule is known as a perceptron, and this rule is called the perceptron learning rule.
例如，某些基本的神经网络，它们的感知器只倾向于学习线形函数(通过划一条线可以把函数输入解析到分类系统中)。
For instance, a certain kind of basic neural network, the perceptron, is biased to learning only linear functions (functions with inputs that can be separated into classifications by drawing a line).
例如，某些基本的神经网络，它们的感知器只倾向于学习线形函数(通过划一条线可以把函数输入解析到分类系统中)。
For instance, a certain kind of basic neural network, the perceptron, is biased to learning only linear functions (functions with inputs that can be separated into classifications by drawing a line).
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