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GGAP-RBF is a sequential learning algorithm so that model can be established dynamically. 该网络的学习算法是串行的,可以进行动态建模。
The model overcomes some flaws of popular learning algorithm such as local minima, slow convergence and initialized values. 该模型克服了传统入侵检测系统所存在的局部极小、收敛速度慢、初值敏感性等问题。
When we play chess, do we use a learning algorithm or brute force. 当我们玩西洋象棋的时候,我们使用学问运算法则或暴力吗。
The paper presents the research of learning algorithm of FNN. 摘要对模糊神经网络的学习方法进行了研究。
With the use of artificial neural network "back propagation" model, the situs structure of neural network is established and the learning algorithm is designed. 摘要运用人工神经网络“反向传播”模型，建立神经网络的拓扑结构，设计相应的网络学习算法；
The Word Sense Disambiguation (WSD) study based on large scale real world corpus is performed using an unsupervised learning algorithm based on DGA improved Bayesian Model. 采用基于依存分析改进贝叶斯网络的无指导的机器学习方法对汉语大规模真实文本进行词义消歧实验。
With the use of artificial neural network “back propagation" model, the situs structure of neural network is established and the learning algorithm is designed. 运用人工神经网络“反向传播”模型,建立神经网络的拓扑结构,设计相应的网络学习算法;
BVM(Ball Vector Machine)is a faster machine learning algorithm than SVM. 球向量机是一种比SVM更快的机器学习方法。
Based on the discussion on learning control method, control model learning in AHS, particular in the important and necessity of online learning, is analyzed. 在讨论了学习控制研究方法和水平的基础上，分析了自动公路系统中控制模型引入学习，尤其是在线学习的重要性和必要性。
This paper presents a method based on the BDI model to implement an informatiion Agent for distribute d multi Agent environments. It also p roposes the model and learning algorithm of the PERFORM(PERsonal inFORmation Man ager)system. 本文提出一种用于分布式多 Agent环境的以 BDI模型为基础构建信息 Agent的方法 ,给出了 PERFORM(PERsonal in FORmation Manager)系统的模型和学习算法
Observational Learning Algorithm (OLA) is an ensemble method based on social learning theory. 观察学习是一种基于社会学习理论的集成学习方法，以往对其研究集中于同构模式。
The learning algorithm can effectively control the unstabl nonlinear system, even if the model of the system is not available and the learner has no a priori experience. 该学习算法在模型未知和没有先验经验的条件下，能通过自身神经网络的在线学习，有效控制不稳定的非线性系统。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed. 摘要提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
We then describe an entropy penalized AMS learning algorithm on Gaussian mixture. 然后，我们描述了另一种基于熵惩罚的自动模型选择学习算法。
Simulation shows that the learning algorithm has a fast convergence speed and good stability. 仿真表明，该学习算法收敛速度快、稳定性好。
The combinational equivalence check methods based on recursive learning algorithm are discussed. 并讨论了基于递归学习的组合电路等价性检验方法；
The model and learning algorithms of BP(Error Back Propagation)network,which is widely applied,is recommended,and RBF(Radial B asis Function)is simply recommended contrastively. 本文首先介绍了神经网络中应用最为成熟广泛的BP网络的模型及其学习算法 ,并简单对比介绍了RBF网络。
NNM can use many learning algorithm .In this paper , it use the modified BP algorithm which proposed by the author . NNM可以采用许多学习算法,前已提及本文中采用作者提出的改进BP算法。
The new method for estimating ore density value with nerual network model is advanced.In this paper,the neural network type,structure and its learning algorithms is presented. 探讨了应用神经网络确定不同品级矿石体重的新方法，建立了该方法的神经网络模型（包括网络类型、网络结构和及其学习算法）。
The future research direction of SVM learning algorithms were proposed. 最后指出了学习算法的研究方向。