| 加权支持向量机在机器状态识别中的应用 |
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| 引用本文： | 杜向华,毛荣富,朱海潮. 加权支持向量机在机器状态识别中的应用[J]. 船海工程, 2006, 35(4): 108-110 |
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| 作者姓名： | 杜向华 毛荣富 朱海潮 |
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| 作者单位： | 海军工程大学振动与噪声研究所,武汉,430033 |
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| 摘 要： | 在机器状态识别中采用加权SVM算法,对类别差异造成的影响进行了相应的补偿,从而提高了小类别的分类精度,这对于需要重点关注小类别精度的应用场合有重要的现实意义,以某减速箱轴承为例,取得了较好的实验结果。
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| 关 键 词： | 支持向量机 分类精度 状态识别 |
| 文章编号： | 1671-7953（2006）04-0108-03 |
| 收稿时间： | 2005-10-13 |
| 修稿时间： | 2005-11-16 |
The application of weighted support vector machine in the machine status identification |
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| Du Xiang-Hua,Mao Rong-fu,Zhu Hai-Chao. The application of weighted support vector machine in the machine status identification[J]. Ship &Ocean Engineering, 2006, 35(4): 108-110 |
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| Authors: | Du Xiang-Hua Mao Rong-fu Zhu Hai-Chao |
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| Affiliation: | Du Xiang-Hua Mao Rong-fu Zhu Hai-ChaoResearch Institute of Vibration and Noise Naval University of Engineering Wuhan 430033 |
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| Abstract: | In order to improve the classification accuracy of the small size sample,the weighted support vector machine(SVM) algorithm is used in the machine status identification.The deceleration gear box experiment results verify the efficiency of the weighted SVM algorithm in mechanical status identification. |
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| Keywords: | support vector machine classification accuracy status identification |
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