提出了新颖的最优模糊聚类神经网络模型对机械手运动轨迹进行控制。
This paper presents a novel framework for trajectory tracking of robotic manipulators based on the optimal fuzzy clusting neural network system.
为了获得滤除噪声和细节保留两方面更好的平衡，提出了一种自适应模糊聚类神经网络。
AFCN (adapted fuzzy cluster neural network) is introduced to keep up trade-off between noise attenuation and detail preservation in image processing.
三是深入研究模糊聚类神经网络的结构优化方法，提出两种模糊聚类神经网络优化方案。
At last we deeply studies the methods of optimizing the structure of fuzzy clustering, and proposes two algorithms.
提出了一种减聚类径向基函数神经网络的纺织空调送风风机故障诊断方法。
A new method of subtractive clustering RBF network for air condition breeze fan fault diagnosis is presented.
在对径向基概率神经网络进行理论分析基础上，采用减法聚类方法确定它的隐中心矢量。
On the basis of analyzing RBPNN in theory, subtractive clustering is used to determine its hidden centric vector.
根据隐含语义索引（LSI）理论和动态自组织映射神经网络理论，提出了一种文本聚类的新方法。
This paper presents a new method of text clustering by using the latent semantic index (LSI) and self-organizing neural network (SNN).
对现有的RBF神经网络进行了分析，并对训练过程中使用的聚类算法进行了改进。
Analysis the current RBF neural network at the same time do some improve work on its training algorithm.
提出了一种新的动态模糊自组织神经网络模型(TGFCM)，并将其用于文本聚类中。
This paper proposed a new model of dynamic fuzzy Kohonen neural network (TGFCM), which was applied to the text clustering.
提出了一种基于模糊超球神经网络聚类与图像处理技术相结合的沉积微相识别方法。
In this paper we propose an automatic sedimentary facies identifying method based on combing fuzzy ellipsoidal neural networks and image process technology.
提出了一种新的模糊聚类方法，构造了分布式模糊神经网络，并重点附述了它们的原理与方法。
A new fuzzy clustering method and a distributed neural network are introduced, and the theory and their applications are stressed.
使用减法聚类和自适应模糊神经网络方法设计了一种水下机器人运动规划器。
By using the methods of subtraction clustering and adaptive fuzzy neural network, a sort of motion planner for the underwater vehicle was designed.
分别使用模糊聚类方法、混合模糊神经网络、关联规则挖掘等知识发现方法对间歇过程中的配方、周期性污垢、操作策略规则等进行挖掘和处理。
Using the Fuzzy Cluster method, Hybrid Fuzzy Neural Network, Association rules mining methods, etc. find and excavate the recipes, periodic fouling, and operation strategy rule in the batch process.
提出了一种免疫聚类径向基函数神经网络(ICRBFNN)模型来预测电力系统短期负荷。
The paper presents an immune clustering RBF neural network (ICRBFNN) model for short-term load forecasting.
模糊聚类是目前知识发现(KDD)领域中的研究分支之一，而神经网络是用于聚类的良好工具。
Fuzzy cluster is one of the branches of knowledge discovery in database (KDD). And neural network is a good tool for clustering.
针对知识发现中的信息模糊查询问题，提出了一种基于神经网络的信息聚类及联想实现方法。
In this paper, a method of information clustering and concept association is shown, it is based on neural network, and it aims at inkling information searching in knowledge discovery.
现在我已经做了对的监督和无监督学习算法，如决策树，一些基本的阅读聚类，神经网络等。
Now I have done some basic reading on supervised and unsupervised learning algorithms such as decision trees, clustering, neural networks... etc.
然后介绍了如何使用模糊聚类算法和等价的前馈神经网络从样本数据中辨识离散的TS模型。
Then we introduce how to identify the TS model from sample data using fuzzy clustering algorithm and equivalent feedforward neural network.
此聚类算法可以在线地划分输入数据，逐点地更新聚类，自己组织模糊神经网络的结构。
This clustering algorithm can on-line partition the input data, pointwise update the clusters, and self-organize the fuzzy neural structure.
为解决相似案例差异性问题，提出了基于划分聚类和模糊神经网络的设计案例相似性检索方法。
To improve the diversity of similar cases, similarity retrieval method based on partitioned clustering and General Fuzzy Min-Max neural network is developed.
结合聚类技术和ART2神经网络技术提出一个基于ART2神经网络的动态风险管理模型。
An ART2-based dynamic risk management model is proposed by using of clustering technique and neural network knowledge.
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.
结合均匀设计和聚类思想提出的样本优选方法，在一定程度上解决了神经网络样本选择的问题。
Based on uniform design and the cluster theory, a optimum selecting method of sample is proposed to solve the problem of sample selection.
本文在分别介绍了传统分类和聚类算法之后，详细分析了基于ART神经网络的聚类算法。
After introducing the traditional methods of classification and clustering, this paper gives a particular analysis of the ART-based clustering method.
在RBF神经网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，从而使神经网络结构得到优化。
A learning algorithm of subtractive clustering method for RBFNN is used to obtain the parameters of radial basis function, so that RBFNN has an optimized structure.
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.
该模型利用模糊聚类技术确定系统的模糊空间和模糊规则数，利用BP算法调整模糊神经网络的权系数。
The fuzzy space and the number of fuzzy rules of this model are defined by the fuzzy clustering method and weight coefficients of the model are adjusted by the BP algorithm.
辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。
The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.
本文试图对自组织映射神经网络（SOM）应用于汉语名词语义自动聚类做某些改进。
This paper tries to make some improvements on applying Self-Organizing-Map (SOM) to automatic clustering of Chinese nouns, so as to generate a better Chinese semantic map.
本文试图对自组织映射神经网络（SOM）应用于汉语名词语义自动聚类做某些改进。
This paper tries to make some improvements on applying Self-Organizing-Map (SOM) to automatic clustering of Chinese nouns, so as to generate a better Chinese semantic map.
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