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art网络
相关语句
  art network
     Feature Weighted Based Category ART Network and Its Application
     基于特征加权的Category ART网络及应用
短句来源
     Application of Fuzzy ART network in fault diagnosis of rolling bearing
     Fuzzy ART网络在滚动轴承故障诊断中的应用
短句来源
     By the application of ART network in the intelligent system for V belt translation,the general structure,backtracking and application of neural network in this system is studied in the paper.
     结合 V 带传动智能 C A D 系统的总体结构、系统回溯等问题,通过 A R T 网络在 V 带传动智能 C A D 系统中的一个具体应用实例,讨论了该系统的结构和网络应用问题
短句来源
     Application of ART network to fault diagnosis for I.C. Engines
     ART网络在内燃机故障诊断中的应用
短句来源
     Evaluation of Oil and Gas Bearing Traps by ART Network Cluster Analysis of Clustered Grey Information
     圈闭含油气性信息灰色聚集ART网络聚类评价法
短句来源
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  art neural networks
     Handwritten Digit Recognition Based on Wavelet Transform and ART Neural Networks
     基于小波变换和ART网络的手写数字识别
短句来源
     Handwritten Digital Recognition Based on Wavelet Transform and ART Neural Networks
     基于小波变换和ART网络的手写数字识别
短句来源
     This dual competition and resonance technique for the input and output nodes establishes a new Fuzzy ART neural network structure to improve the memory stability in traditional Fuzzy ART neural networks.
     该模型将输入节点的竞争共振机制引入到输出类别节点,采用输入节点和输出节点双重竞争共振机制,形成了一种新的模糊ART结构,解决了传统模糊ART网络记忆不稳定问题.
短句来源
  “art网络”译为未确定词的双语例句
     Recognition on fault of transformer coil hot-spot using Fuzzy ART
     基于Fuzzy ART网络识别变压器绕组过热故障
短句来源
     Application of ART in Fault Diagnosis in Diesel Engines
     ART网络在柴油机故障诊断中的应用
短句来源
     The neural network, Fuzzy ART, and its algorithm are introduced, and used to classify patterns and detect anomaly for system calls sequence of Linux process.
     介绍了一种模糊神经网络Fuzzy ART及其实现,利用Fuzzy ART网络对Linux进程的系统调用序列进行模式提取,并据此进行异常检测。
短句来源
     A New ART Neural Network for Remote-Sensing Image Classification
     一种新的ART网络遥感影像分类方法
短句来源
     Experiments on the UCI datasets show that the FWART has better generalization power than Category ART.
     在UCI标准数据集上的实验表明,FWART网络获得了比Category ART网络更好的泛化能力。
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  art network
2-D Shape Recognition using Recursive Landmark Determination and Fuzzy ART Network Learning
      
This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer.
      
This paper describes a 'state-of-the-art' network planning tool-kit for core transmission systems.
      
Results showed no difference between decisions regarding treatment by the ART network and by the experts.
      
After successful training of the ART network, an unwanted salient area is inhibited by the vigilance value of the ART network.
      
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  art neural networks
Adaptive resonance theory (ART) neural networks are known for their plastic and stable learning of categories, hence providing an answer to the so called stability-plasticity dilemma.
      
In this paper, we present an improved stabilization strategy for ART neural networks that does not suffer from this problem and that produces a soft-clustering solution as a positive side effect.
      
The image-processing system employs the adaptive resonant theory (ART) neural networks to classify the outer shape of the measured object.
      
This article clearly demonstrates that state-of-the-art neural networks can be used in automatic test equipment for iterative diagnosis of electronic circuit board malfunctions.
      
Furthermore, ART neural networks have the added advantage over the backpropagation neural network and decision trees that they can learn online.
      
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This paper is based on Hamming memory neural network and Adaptive Resonance Theory (ART) model. In theory, we analyzes defects of the Hamming network algorithm. We utilized the idea of ART and developed a fast classification algorithm, called improved hamming algorithm (Im-H Algorithm). This algorithm provides two important properties of updating the thresholds and imtroducing empirical iterations. We have applied this methed to character recognition. A large number of experiments demonstrate its efficiency...

This paper is based on Hamming memory neural network and Adaptive Resonance Theory (ART) model. In theory, we analyzes defects of the Hamming network algorithm. We utilized the idea of ART and developed a fast classification algorithm, called improved hamming algorithm (Im-H Algorithm). This algorithm provides two important properties of updating the thresholds and imtroducing empirical iterations. We have applied this methed to character recognition. A large number of experiments demonstrate its efficiency and its high covergence rate.

本文以海明神经网络与自适应谐振理论(ART)模型学习算法为基础,从理论上分析了海明网络学习算法的缺陷,利用ART网络的思想,提出了一种快速分类的神经元网络的算法,命名为Improved Hamming算法(简称Im-H算法)。此算法主要优点在于阈值更新及引入了经验迭代次数。将此算法用于字符模式识别,大量的计算机实验结果表明了Im-H网络学习算法的有效性、快速性。

The possibility of applying the artificial neural network theory to low andzero resistance insulator diagnosis is investigated.The corona pulse current isused as the characteristic values and the Hamming network is employed tofilter out the noise of the collected wave form, then the ART network is usedto recognize the filtered wave form. Case study shows the method proposedhere can put the wave forms collected into cluster correctly.

本文探讨了应用人工神经网络进行高压输电线路中低零值绝缘子检测的可行性。该方法以电晕电流做为特征量,首先利用Hamming网络对采集到的波形进行噪声过滤,然后,使用ART网络对过滤后的波形进行辨识,试算表明,本文提出的方法可对各种情况的波形进行正确的辨识,该研究可为低零值绝缘子的在线监测打下理论基础。

One of main shortcommings for widely useful potencyARTnetworkis thatthe value of vigilance parameter is completely dependent on user'sexperience,and up to today,there are no any theory and method to guide researchers, In thispaper a great number of pattern samples are respectively sampled in Monte Carloway, and optimal division of samples is realized in a method of reference[3]。Based on optimal division,every sample is orderlv fed into ART network,and atthe same time,the vigilance parameter has to be corrected...

One of main shortcommings for widely useful potencyARTnetworkis thatthe value of vigilance parameter is completely dependent on user'sexperience,and up to today,there are no any theory and method to guide researchers, In thispaper a great number of pattern samples are respectively sampled in Monte Carloway, and optimal division of samples is realized in a method of reference[3]。Based on optimal division,every sample is orderlv fed into ART network,and atthe same time,the vigilance parameter has to be corrected until a precise classifi-cation is established. The vigilance parameters versus variant category numbersare fit as a formula in LSM so that the technique difficulty to find better vigi-lance parameter has been solved.

具有广泛应用潜力的ART网络的主要缺陷之一,是其警戒线参数的取值大小完全依赖使用者的经验,迄今无有理论及方法上的指导;本文分别通过蒙特卡洛抽样来获取大量模式样本、并应用模糊聚类的优化分割技术进行最佳分类;然后,在最佳分类的基础上,将模式样本序贯输入ART网络,同时调整警戒线参数,直至建立起准确的分类器;最后,将不同分类数下对应的譬戒线参数拟合成经验公式,从而为给定分类数下较准确获取警戒线参数解决了重要的技术困难。

 
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