Network learning has increasingly become an important means for people to acquire knowledge and solve problems.
网络学习已日益成为人们获取知识和解决问题的重要手段。
LM learning algorithm is adopted in BP network learning.
BP网络的学习采用了LM学习算法。
The important characteristic of network learning is the learners' independence.
网络学习的重要特征是学习者的自主性。
High quality resource classes and network learning space for everyone are the application tasks.
“优质资源班班通”和“网络学习空间人人通”都是应用任务。
An effective network learning method is formed by combining GA, BP algorithms with fuzzy logic system.
将模糊逻辑系统、GA算法与BP算法相结合，形成一种有效网络学习方法。
The easy-to-use interface allows you to set minimal conditions for preprocessing and neural network learning.
易于使用的界面，使您能够设置最小的条件进行预处理和神经网络学习。
Among it, supplying the personalized support is the effective approach for improving network learning quality.
而其中提供个性化的支持是提高网络自主学习质量的有效途径。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
The results show that the model has a great efficiency of network learning and a high accuracy of prediction and judgement.
实际应用表明：该模型大大提高了网络的学习效率和预测评判的精度，可以作为油气集输管道腐蚀速率预测的良好工具。
We collect the network learning material with view to the young learners actual language receptivity and psychological character.
栏目的收编内容均为针对少儿的实际语言接受能力和心理特点的，适合网络学习的精选内容。
This method can avoid the problems of depending on a large number of data with high quality in existing Bayesian network learning.
该方法可避免现有的贝叶斯网络学习过于依赖数据、对数据的数量和质量要求过高等问题。
A personality mining method is proposed to obtain the personality characteristics of learners automatically in the network learning.
提出了一种面向个性化网络学习的学习者个性挖掘方法，以实现网络学习中学习者个性特征的自动获取。
The system comprises teaching, network learning, graduation project and electronic design competition, which form a feedback teaching system.
结合课堂教学、网络学习的特点，分别提出采用任务驱动法和及时教学法；
Building relative capital, improving relative scope and utilizing hard restriction, such as bargain, institution, will help network learning.
有效的网络学习应建立合理资本，提高合理范围，还必须借助于合同、制度等硬约束方式。
The experimental results show that the network learning speed can be increased and the nonlinear errors of the sensors can be reduced by using BPNN.
实验结果表明采用BP神经网络可以提高网络收敛速度，大大减小传感器线性误差。
Information technology has formed network learning environment, digital learning resources and digital learning model after it was utilized in education.
信息技术应用到教育教学过程后，形成了网络化的学习环境、数字化的学习资源、数字化的学习方式。
The Micro-level strategy is the "Auxiliary" of E-learning strategies, as a"tactic" to be directly used to guide specific process of the network learning.
微观层次策略是网络学习策略之“辅”，是作为一种学习的“战术”，直接用来指导具体的网络学习过程。
Specifies the percentage of training cases used to calculate the holdout error, which is used as part of the stopping criteria during neural network learning.
指定用于计算？效组错误的培训案例之百分比，以在类神经网路学习期间作为停止准则的一部分。
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。
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。
It can not only reduce the network learning cycle, but also optimize the network structure by using Kalman filter to adjust of the parameters of the neural network.
利用卡尔曼滤波调整神经网络的参数，不仅可以减少网络的学习周期，而且可以优化网络的结构。
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。
After analyzing the superiority and deficiency of network learning environment of the day, this paper presents an "Intelligent Interactive Network learning Environment".
本文在分析了当前网络学习环境存在的优势和不足之处后，提出了“智能交互式网络学习环境”的设计与开发问题。
The main factors of network learning have been analyzed in detail, and the factor extraction method using MA is put forward according to network study pattern recognition.
详细分析了网络学习模式中的主要因素，针对网络学习模式识别提出了使用移动代理（MA）进行因素提取的方法。
The main factors of network learning have been analyzed in detail, and the factor extraction method using MA is put forward according to network study pattern recognition.
详细分析了网络学习模式中的主要因素，针对网络学习模式识别提出了使用移动代理（MA）进行因素提取的方法。
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