Network structure is adjusted with networks parameter learning, which could reduce error.
在网络参数学习的同时网络结构也在进行调整，使得误差不断减小。
In the process of modeling BNs, the structure learning and parameter learning of BNs are analyzed detailedly.
详细分析了贝叶斯网络的建模过程，即贝叶斯网络的结构学习过程和贝叶斯网络的参数学习过程。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed.
分析了动态递归神经网络系统辨识的参数学习算法。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed. D.
分析了动态递归神经网络系统辨识的参数学习算法。
The natural gradient method is applied for parameter learning of the linear and nonlinear parts of the separating system.
分离系统的线性部分和非线性部分参数学习都采用自然梯度算法。
Finally, the construction of discrete scaling and wavelet kernels, the kernel selection and the kernel parameter learning are discussed.
最后讨论了离散尺度与小波核函数的构造，核函数选择与核参数学习。
The learning of Bayesian Networks is studied, including structure learning of Bayesian Networks and parameter learning of Bayesian Networks.
研究了贝叶斯网络的学习问题，包括贝叶斯网络结构学习和贝叶斯网络参数学习。
Meanwhile, parameter learning algorithm of the membership function is developed. Both of them improve diagnostic rules as well as learning properties.
提出了部分层学习算法，并推导出隶属度函数的参数学习算法，改善了诊断规则和学习性能。
By using this model, people need not select any fuzzy logic in advance, and can adjust the network structure by the structure and parameter learning of the neural network.
该模型无需事先确定模糊控制规则，并能通过神经网络的结构及参数学习调整模糊神经网络的结构。
The SOAP request begins with the business logic of your application learning the method and parameter to call from a Web Services Description Language (WSDL) document.
一个SOAP请求从应用程序的业务逻辑开始，从Web服务描述语言(WSDL)文档中获得调用方法和参数。
When learning computer programming, I found it helpful to look at a function like a pencil sharpener. A parameter was a dull pencil, inside processes sharpened and returned a sharp pencil.
我在学编程时，常把程序比作卷笔刀，而把参数比作钝铅笔，经过处理我们就得到尖铅笔了。
The research boundary is decided by the vigilance parameter , which decreases with the learning process in order to get the high accuracy and the stability of networks.
警戒参数决定了节点调整的搜索范围，随学习过程进行，节点搜索范围变小，保证了分类精度和网络的稳定性；
This paper combines learning theory with robust control and discusses robust control design problems involving real parameter uncertainty in control systems based on randomized algorithms.
将学习理论与鲁棒控制相结合，采用随机化算法针对实参数不确定系统讨论了鲁棒控制器的设计问题。
Then in allusion to these two important factors, a concept of incremental learning and a loss extent parameter are put forward in this paper, and Native Bayesian Classification.
文中针对该算法这两个最主要的缺陷，提出增量学习概念，引入损失幅度参数，改进和完善朴素贝叶斯分类算法。
Simulation results of contrapose Bioreactor show that the proposed method can accelerate learning process and is robust to larger parameter changes.
生化反应器定值控制的仿真结果表明，该方法加快了学习过程，并对更大范围的参数变化具有鲁棒性。
A new type of adaptive PID controller using diagonal recurrent neural network (DRNN) is presented. An on-line learning algorithm based on PID parameter self-tuning method is given.
提出了一种基于对角回归神经网络的PID控制器结构，给出了PID参数在线自整定的学习控制算法。
The learning parameter adjusts adaptively with the affinity to promote the global search ability.
提出了根据算法亲合度自适应调节学习参数的方法，以提高算法的全局寻优能力。
Taking the 1975-2006 National passenger traffic data and other related indicators as a learning sample, then verify the validity of the training model after Parameter Optimization.
把1975到2006年全国的客运量数据和其他相关指标作为学习样本，验证寻优参数得到训练模型预测结果的可靠性。
A learning model with hybrid intelligence for the electrical parameter in EDM which imitates a decision making process of a skilled operator was described.
提出了一个基于混合智能的电火花加工电参数学习模型，它模仿熟练操作者的决策过程，由工艺数据库、加工规则库、学习模块和推理模块组成。
Using the capacity of arbitrary nonlinear expressiveness, neural network can help to achieve the best control through learning systemic performance and adjusting automatically PID parameter.
利用神经网络的任意非线性表达能力，通过对系统的学习来调整PID参数，实现最优的PID控制。
The Defence model based on switching formation applies Case-based learning to design formations breaching the experiential parameter method.
基于阵形变换的防守模型，将案例学习应用到阵形设计中，突破了单凭直接经验设置阵形的方式。
The method of establishing on-line temperature prediction model, set point model and parameter tracing self-learning model of computerized heat recovery processing control system is introduced.
介绍了余热处理计算机控制系统的在线温度预报模型、设定模型和参数跟踪自学习模型的建立方法。
The learning parameter is set as 0.01 and the training iteration is taken as 500.
神经网络模型的学习参数为0.01，网络训练迭代次数为500。
The PNN structure was optimized based on statistical results from the PCA for the training samples. A learning algorithm was introduced into the PNN to reduce uncertainties parameter.
以概率乘法公式为理论依据，根据训练样本的PCA结果对PNN进行结构优化，并引入学习算法减小PNN的参数不确定性。
The learning rate is an important parameter for the learning process of a neural network (NN) which influents the stability and quickness of the NN.
学习速率是控制神经网络学习过程的一个重要参数，影响神经网络的稳定性和快速性。
When still object detection is a less requirement, configure this parameter to a higher value to increase background learning speed to prevent scene-change induced error rates.
若无侦测静止物件的需求，较高的学习速度可减少场景变化所造成的误判。
The PID controller based on BP neural networks is designed to realize control parameter self-learning and self-adjusting.
设计了基于BP神经网络的PID控制器，实现PID控制器参数自学习、自整定。
Aiming at this question, this paper proposes a parameter model under evidence loss and deduce an EM updating algorithm which contains learning rate.
针对这样的问题，本文提出一种证据丢失参数模型，并推导出包含学习率的EM更新算法。
Aiming at this question, this paper proposes a parameter model under evidence loss and deduce an EM updating algorithm which contains learning rate.
针对这样的问题，本文提出一种证据丢失参数模型，并推导出包含学习率的EM更新算法。
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