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INTRODUCTION The failure of machinery reduces the productionrate and increases the costs of production and maintenance.Therefore,it is important to reduce maintenance costs and prevent unscheduled downtimes fomachinery.So knowledge of what,where and howfaults occur is very important.Condition-basedmaintenance(CBM)has the potential to decreaselife-cycle maintenance costs,increase operationareadiness and improve safety.Fault detection andfailure mode diagnosis are also necessary for implem… 相似文献
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文中深入讨论了利用支持向量机构造多分类器的方法,并比较了它们的优缺点,提出了基于赫夫曼树的SVM多分类构造算法,并在训练时间及判别时间上证明了该构造算法的优越性,减少了分类器的判别时间. 相似文献
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Currently there are two approaches for a multi-class support vector classifier （SVC）. One is to construct and combine several binary classifiers while the other is to directly consider all classes of data in one optimization formulation. For a K-class problem （K〉2）, the first approach has to construct at least K classifiers, and the second approach has to solve a much larger optimization problem proportional to K by the algorithms developed so far. In this paper, following the second approach, we present a novel multi-class large margin classifier （MLMC）. This new machine can solve K-class problems in one optimization formulation without increasing the size of the quadratic programming （QP） problem proportional to K. This property allows us to construct just one classifier with as few variables in the QP problem as possible to classify multi-class data, and we can gain the advantage of speed from it especially when K is large. Our experiments indicate that MLMC almost works as well as （sometimes better than） many other multi-class SVCs for some benchmark data classification problems, and obtains a reasonable performance in face recognition application on the AR face database. 相似文献
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Due to e-business's variety of customers with different navigational patterns and demands, multi-class queuing network is a natural performance model for it. The open multi-class queuing network(QN) models are based on the assumption that no service center is saturated as a result of the combined loads of all the classes. Several formulas are used to calculate performance measures, including throughput, residence time, queue length, response time and the average number of requests. The solution technique of closed multi-class QN models is an approximate mean value analysis algorithm (MVA) based on three key equations, because the exact algorithm needs huge time and space requirement. As mixed multi-class QN models, include some open and some closed classes, the open classes should be eliminated to create a closed multi-class QN so that the closed model algorithm can be applied. Some corresponding examples are given to show how to apply the algorithms mentioned in this article. These examples indicate that multi-class QN is a reasonably accurate model of e-business and can be solved efficiently. 相似文献
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支持向量机方法是一种基于统计学理论的机器学习的新方法,它在解决小样本,非线性及高维模式识别中表现出许多特有的优势。目前它主要用于二元分类问题中,而对于其在多类分类应用仍是一个值得研究的问题。在目前存在的各种多类支持向量机分类问题中,一对一方法是一种最符合实际的方法。本文提出了一种改进的支持向量机,并将其应用于图像分割。这种改进的支持向量机它对一对一方法进行了改进,实验表明,支持向量机的方法是一种很有潜力的图像分割技术。 相似文献
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支持向量机方法在解决小样本,非线性及高维模式识别中表现出许多特有的优势。目前主要用于二元分类问题中,而对于其在多类分类应用仍是一个值得研究的问题。在目前存在的各种多类支持向量机分类问题中,一对一方法是一种最符合实际的方法。文章提出了一种改进的支持向量机,并将其应用于图像分割。这种改进的支持向量机它对一对一方法进行了改进,实验表明,支持向量机的方法是一种很有潜力的图像分割技术。 相似文献
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Joint application of feature extraction based on EMD-AR strategy and multi-class classifier based on LS-SVM in EMG motion classification 总被引：2，自引：0，他引：2
YAN Zhi-guo WANG Zhi-zhong REN Xiao-mei 《浙江大学学报(A卷英文版)》2007,8(8):1246-1255
This paper presents an effective and efficient combination of feature extraction and multi-class classifier for motion classification by analyzing the surface electromyografic(sEMG) signals. In contrast to the existing methods,considering the non-stationary and nonlinear characteristics of EMG signals,to get the more separable feature set,we introduce the empirical mode decomposition(EMD) to decompose the original EMG signals into several intrinsic mode functions(IMFs) and then compute the coefficients of autoregressive models of each IMF to form the feature set. Based on the least squares support vector machines(LS-SVMs) ,the multi-class classifier is designed and constructed to classify various motions. The results of contrastive experiments showed that the accuracy of motion recognition is improved with the described classification scheme. Furthermore,compared with other classifiers using different features,the excellent performance indicated the potential of the SVM techniques embedding the EMD-AR kernel in motion classification. 相似文献
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张光明 《当代教育理论与实践》2021,13(1):42-47
片段教学是一种快速、高效、直观、综合的授课模式。但目前部分中学英语教师对片断教学认识模糊,在片断教学设计和实施中存在困惑。从片断教学的内涵和实践出发,结合实例,从教学时间、教学环节、教学内容、教学方法、教学手段、教学艺术、板书设计六个方面对片断教学设计给出具体建议。根据中学英语教学的实际需求,提出基于片断教学的中学英语分层分类走班课程和线上课程的开发思路与实践途径,以期为中学英语教师提供片断教学实践参考。 相似文献
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结合Gabor小波变换的特征提取算法提出了一种基于决策模板的多分类支持向量机.该方法在对JAFFE基本表情数据库进行训练并测试时获得了较高的正确率,实验结果表明该方法是一种有效的表情识别算法. 相似文献
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线性判别分析(Linear Discriminant Analysis,LDA)是用于降维和分类的方法,然而在遇到小样本问题时,由于全局散布矩阵是奇异的,所以传统的LDA方法是不适用的。为了解决LDA的这种缺点,提出了基于最小二乘线性判别分析(Least Squares Linear Discriminant Analysis,LS-LDA)的正则化算法,在LS-LDA中分别加入关于加权矩阵的L1范数、L2范数和弹性网络的惩罚项、来解决小样本问题,使模型具有鲁棒性和稀疏性。在对回归分析、正则化方法和LS-LDA相关技术进行深入分析的基础上,构建正则化最小二乘线性判别分析框架算法,实现数据降维。结合标准文本数据集进行实验,采用KNN(K-Nearest-Neighbor)分类器进行文本分类。实验结果表明,正则化的LS-LDA具有很好的分类性能,其中以加入了弹性网络惩罚项的LS-LDA最优。 相似文献
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A fault diagnosis model is proposed based on fuzzy support vector machine (FSVM) combined with fuzzy clustering (FC).Considering the relationship between the sample point and non-self class,FC algorithm is applied to generate fuzzy memberships.In the algorithm,sample weights based on a distribution density function of data point and genetic algorithm (GA) are introduced to enhance the performance of FC.Then a multi-class FSVM with radial basis function kernel is established according to directed acyclic graph algorithm,the penalty factor and kernel parameter of which are optimized by GA.Finally,the model is executed for multi-class fault diagnosis of rolling element bearings.The results show that the presented model achieves high performances both in identifying fault types and fault degrees.The performance comparisons of the presented model with SVM and distance-based FSVM for noisy case demonstrate the capacity of dealing with noise and generalization. 相似文献
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为指导人们正确地认识随机事件,引导人们适当抑制盲目应对随机事件的冲动。该文选取一个独特的视角,讨论概率统计中的小概率事件,拆解概率理论,分析中奖概率,并就概率论联系实际,培养统计思维,提高学生的应用能力等方面,探讨了通过生活中的数学问题增强对实际事物中随机性的敏感,培养学生概率直觉思维,提高学生的应用能力,培养创新人才的途径。 相似文献
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研究了公交车和私家车相互作用下的排队网络在高峰时段随时间变化的最优拥挤收费问题.将时空拓展网络(STEN)与传统的网络平衡模型技术相结合,建立了多用户类型、多模式和多准则交通网络平衡模型.不同类型的用户具有不同的时间价值(VOTs),同一类用户根据出行时间和成本的不同权重确定出行负效用或一般出行成本.此外,将对称成本函... 相似文献
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随机变量的概率分布是概率论和数理统计教学中的最基本的概念,在一般的教学过程中一般都是孤立地阐述各种概率分布.为使学生建立起常用概率分布之间以及离散型和连续型概率分布之间的联系,对常用6种离散型概率分布和11种连续型概率分布的关系加以讨论,在侯文建立的概率分布的关系图的基础上,从另一个角度归纳并补充了常用概率分布之间的关... 相似文献
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This paper presents an effective method for motion classification using the surface electromyographic (sEMG) signal collected
from the forearm. Given the nonlinear and time-varying nature of EMG signal, the wavelet packet transform (WPT) is introduced
to extract time-frequency joint information. Then the multi-class classifier based on the least squares support vector machine
(LS-SVM) is constructed and verified in the various motion classification tasks. The results of contrastive experiments show
that different motions can be identified with high accuracy by the presented method. Furthermore, compared with other classifiers
with different features, the performance indicates the potential of the SVM techniques combined with WPT in motion classification. 相似文献
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本文对条件概率进行补充说明.将条件概率看作事件域上的二元函数,并研究了其性质.指出了条件概率是事件域上的一种包含度.借助于条件概率的包含度解释,我们给出全概率公式的另一种理解. 相似文献
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概率卷积在现代数字通信系统等领域具有重要而又基础的作用.首先介绍用于有限域下的概率卷积的组合搜索法和FFT法;然后提出一种基于有限域设计的通用概率卷积算法,基于有限域运算,用递归的求解方法实现提出的通用概率卷积算法.通过算例、实验和比较分析,讨论了三种算法在有限域概率卷积中的优缺点.分析发现在小规模的有限域下的概率卷积,通用法与FFT法相比,计算复杂度相当但更通用;在大规模概率卷积情况下,通用算法比FFT更通用,比组合搜索法更有效. 相似文献