• A new method of fault classification for mechanical system by means of support vector machine (SVM) is proposed and a multi-class SVM classifier based on binary classification was developed.

    提出了一种利用支持向量(SVM)机械系统故障进行分类方法值分类为基础,开发了基于支持向量机的多值分类

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  • Aiming at the pattern recognition of traffic flows in elevator group control systems, a method based on the multi-value classification SVM (Support Vector Machine) is put forward.

    针对电梯调度中的交通模式识别问题,提出了一种基于分类支持向量电梯交通流模式识别方法

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  • This paper introduces "one-against-one" approach, which is a multi-class classification method of SVM.

    在两类分类基础上介绍一种基于SVM的多类分类算法———一对一分类法,将其用于中国茶叶的分类。

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  • The twin screw extruder fault diagnosis by multi-fault classifier based on SVM is mainly discussed and the retest proves that this SVM really has preferable ability of classification.

    诊断实例表明基于支持向量机的多故障分类器对设备故障具有好的分类效果。

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  • The problems and defections of the existing methods of SVM multi-class classification were analyzed. A multi-class classification based on binary tree was put forward.

    介绍了几种常用支持向量机多类分类方法分析存在问题缺点

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  • The presented multi-class SVM is of better classification ability and can solve the unclassifiable region problems int.

    新的多类SVM在一定程度上解决传统投票决策方法的不可分区域问题,因此具有更好分类性能。

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  • We solve the multi-classification task by using a so called Coding SVM. By using this algorithm, we not only solve the classification task but also reduce the training and testing time.

    采用一种基于编码支持向量机的多分类方法,方法解决SVM多分类问题的同时,有效地减少训练测试时间,提高了算法的效率。

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  • SVM can only deal with the two-sample problem and can do nothing for the multi-classification problem.

    SVM只能解决二类样本问题无法解决实际情况中的多类分类问题。

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  • Secondly, the text studies the Statistical Learning Theory(STL) and Support Vector Machine(SVM)theory seriously, discusses multi-category classification algorithms of SVM.

    其次认真研究统计学习理论的主要内容SVM算法的基本原理,并且就SVM的多种多类别分类算法分别加以讨论

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  • Simple SVM can only handle binary classification problems; can not directly handle multi-value classification.

    简单支持向量机只能处理二值分类问题不能直接处理多分类问题。

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  • In the real world most of the data is multi-class data, so the simple SVM need for further expansion, so that it can solve the multi-value classification.

    现实世界中的大部分数据都是多类数据,所以需要简单支持向量机进一步扩展使解决分类问题。

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  • Finally, a method based on sub-band feature extraction and Support Vector Machine with Binary Tree Architecture (SVM-BTA) is presented for power quality disturbances multi-classification.

    最后提出基于子频带特征提取二叉结构支持向量相结合的电能质量多分类方法。

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  • Finally, a method based on sub-band feature extraction and Support Vector Machine with Binary Tree Architecture (SVM-BTA) is presented for power quality disturbances multi-classification.

    最后提出基于子频带特征提取二叉结构支持向量相结合的电能质量多分类方法。

    youdao

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